A B C D E F G H I J K L M N O P Q R S T U V W X Y

A

absoluteDifference(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns |c1 - c2|.
absolutelyDiscountedDistribution(Counter<E>, int, double) - Static method in class edu.stanford.nlp.stats.Distribution
 
AbstractCachingDiffFunction - Class in edu.stanford.nlp.optimization
 
AbstractCachingDiffFunction() - Constructor for class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
AbstractCounter<E> - Class in edu.stanford.nlp.stats
Default implementations of all the convenience methods provided by Counter.
AbstractCounter() - Constructor for class edu.stanford.nlp.stats.AbstractCounter
 
AbstractIterator<E> - Class in edu.stanford.nlp.util
Iterator with remove() defined to throw an UnsupportedOperationException.
AbstractIterator() - Constructor for class edu.stanford.nlp.util.AbstractIterator
 
AbstractLinearClassifierFactory<L,F> - Class in edu.stanford.nlp.classify
Shared methods for training a LinearClassifier.
AbstractLinearClassifierFactory() - Constructor for class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
 
AbstractStochasticCachingDiffFunction - Class in edu.stanford.nlp.optimization
 
AbstractStochasticCachingDiffFunction() - Constructor for class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
AbstractStochasticCachingDiffFunction.SamplingMethod - Enum in edu.stanford.nlp.optimization
 
AbstractStochasticCachingDiffUpdateFunction - Class in edu.stanford.nlp.optimization
Function for stochastic calculations that does update in place (instead of maintaining and returning the derivative) Weights are represented by an array of doubles and a scalar that indicates how much to scale all weights by This allows all weights to be scaled by just modifying the scalar
AbstractStochasticCachingDiffUpdateFunction() - Constructor for class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffUpdateFunction
 
accept(T) - Method in interface edu.stanford.nlp.util.Filter
Checks if the given object passes the filter.
accuracy(Iterator<RVFDatum<L, F>>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
accuracy() - Method in class edu.stanford.nlp.classify.PRCurve
 
AccuracyStats<L> - Class in edu.stanford.nlp.stats
Utility class for aggregating counts of true positives, false positives, and false negatives and computing precision/recall/F1 stats.
AccuracyStats(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>, L) - Constructor for class edu.stanford.nlp.stats.AccuracyStats
 
AccuracyStats(L, String) - Constructor for class edu.stanford.nlp.stats.AccuracyStats
 
AdaptedGaussianPriorObjectiveFunction<L,F> - Class in edu.stanford.nlp.classify
Adapt the mean of the Gaussian Prior by shifting the mean to the previously trained weights
AdaptedGaussianPriorObjectiveFunction(GeneralDataset<L, F>, LogPrior, double[][]) - Constructor for class edu.stanford.nlp.classify.AdaptedGaussianPriorObjectiveFunction
 
adaptFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
NER adaptation (Gaussian prior) parameters.
adaptSigma - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
adaptWeights(Dataset<L, F>, LinearClassifierFactory<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
adaptWeights(double[][], GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Adapt classifier (adjust the mean of Gaussian prior) under construction -pichuan
add(Datum<L, F>) - Method in class edu.stanford.nlp.classify.Dataset
 
add(Collection<F>, L) - Method in class edu.stanford.nlp.classify.Dataset
 
add(Collection<F>, L, boolean) - Method in class edu.stanford.nlp.classify.Dataset
 
add(int[], int) - Method in class edu.stanford.nlp.classify.Dataset
Adds a datums defined by feature indices and label index Careful with this one! Make sure that all indices are valid!
add(Datum<L, F>) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
add(Datum<L, F>) - Method in class edu.stanford.nlp.classify.RVFDataset
 
add(Datum<L, F>, String, String) - Method in class edu.stanford.nlp.classify.RVFDataset
 
add(Datum<L, F>) - Method in class edu.stanford.nlp.classify.WeightedDataset
 
add(Collection<F>, L) - Method in class edu.stanford.nlp.classify.WeightedDataset
 
add(Datum<L, F>, float) - Method in class edu.stanford.nlp.classify.WeightedDataset
 
add(Collection<F>, L, float) - Method in class edu.stanford.nlp.classify.WeightedDataset
 
add(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
add(float[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
add(E) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Unsupported Operation.
add(Object) - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Adds an Object to the underlying Collection of input sources.
add(double, double[], double[], int) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
add(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
add(E) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Adds an object to the queue with the minimum priority (Double.NEGATIVE_INFINITY).
add(E, double) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Convenience method for if you want to pretend relaxPriority doesn't exist, or if you really want add's return conditions.
add(E, double) - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Adds a key to the queue with the given priority.
add(E) - Method in class edu.stanford.nlp.util.HashIndex
Adds an object to the Index.
add(E) - Method in interface edu.stanford.nlp.util.Index
 
add(int) - Method in class edu.stanford.nlp.util.IntUni
 
add(E, double) - Method in interface edu.stanford.nlp.util.PriorityQueue
Convenience method for if you want to pretend relaxPriority doesn't exist, or if you really want add's return conditions.
addAll(Iterable<? extends Datum<L, F>>) - Method in class edu.stanford.nlp.classify.GeneralDataset
Adds all Datums in the given collection of data to this dataset
addAll(Collection<? extends E>) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Unsupported Operation.
addAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Adds all Objects in Collection c to the underlying Collection of input sources.
addAll(Counter<E>) - Method in class edu.stanford.nlp.stats.AbstractCounter
Adds the counts in the given Counter to the counts in this Counter.
addAll(Counter<E>) - Method in class edu.stanford.nlp.stats.ClassicCounter
Adds the counts in the given Counter to the counts in this Counter.
addAll(Counter<E>) - Method in interface edu.stanford.nlp.stats.Counter
Adds the counts in the given Counter to the counts in this Counter.
addAll(IntCounter<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Adds the counts in the given Counter to the counts in this Counter.
addAll(TwoDimensionalCounterInterface<K1, K2>) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
addAll(K1, Counter<K2>) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
addAll(Collection<T>, Iterable<? extends T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Add all the items from an iterable to a collection.
addAll(Collection<? extends E>) - Method in class edu.stanford.nlp.util.HashIndex
Adds every member of Collection to the Index.
addAll(Collection<? extends E>) - Method in interface edu.stanford.nlp.util.Index
 
addChild(LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
addFeatureIndices(int[]) - Method in class edu.stanford.nlp.classify.Dataset
 
addFeatures(Collection<F>) - Method in class edu.stanford.nlp.classify.Dataset
 
addFeatures(Collection<F>, boolean) - Method in class edu.stanford.nlp.classify.Dataset
 
addInPlace(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Increases the values in this array by b.
addInPlace(float[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Increases the values in this array by b.
addInPlace(Counter<E>, Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of target to be target[k]+scale*arg[k] for all keys k in target.
addInPlace(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of target to be target[k]+arg[k] for all keys k in arg.
addInPlace(double[], Counter<E>, Index<E>) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of double[] target to be target[idx.indexOf(k)]+a.getCount(k) for all keys k in arg
addInPlace(TwoDimensionalCounter<T1, T2>, TwoDimensionalCounter<T1, T2>, double) - Static method in class edu.stanford.nlp.stats.Counters
For all keys (u,v) in arg, sets target[u,v] to be target[u,v] + scale * arg[u,v]
addInPlace(TwoDimensionalCounter<T1, T2>, TwoDimensionalCounter<T1, T2>) - Static method in class edu.stanford.nlp.stats.Counters
For all keys (u,v) in arg, sets target[u,v] to be target[u,v] + arg[u,v]
addInPlace(Counter<E>, Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of target to be target[k]+ num-of-times-it-occurs-in-collection if the key is present in the arg collection.
addInPlace(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Increments all keys in a Counter by a specific value.
addIntervalRelationFlags(int, boolean) - Method in class edu.stanford.nlp.util.Interval
 
addLabel(L) - Method in class edu.stanford.nlp.classify.Dataset
 
addLabel(LabelType) - Method in class edu.stanford.nlp.ling.BasicDatum
Adds the given Label to the List of labels for this Datum if it is not null.
addLabelIndex(int) - Method in class edu.stanford.nlp.classify.Dataset
 
addLoggingClass(String) - Static method in class edu.stanford.nlp.util.logging.Redwood
Add a class to the list of known logging classes.
addMultInPlace(double[], double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Add c times the array b to array a.
addMultInto(double[], double[], double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
addRandomColors - Variable in class edu.stanford.nlp.util.logging.OutputHandler
 
addToKeySet(E) - Method in class edu.stanford.nlp.stats.Distribution
Insures that object is in keyset (with possibly zero value)
ADMath - Class in edu.stanford.nlp.math
The class ADMath was created to extend the current calculations of gradient to automatically include a calculation of the hessian vector product with another vector v.
ADMath() - Constructor for class edu.stanford.nlp.math.ADMath
 
after() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the whitespace String after the word.
after() - Method in interface edu.stanford.nlp.ling.HasContext
Return the whitespace String after the word.
allIndices - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
alsoHide(Object) - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Show all the channels currently being printed, with the exception of this new one
alsoShow(Object) - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Show all the channels currently being printed, in addition to a new one
altAnswerFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
annealingRate - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
annealingType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
AnnotationLookup - Class in edu.stanford.nlp.ling
 
AnnotationLookup.KeyLookup - Enum in edu.stanford.nlp.ling
 
announceObjectBankEntries - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ansiCode - Variable in enum edu.stanford.nlp.util.logging.Color
 
ansiCode - Variable in enum edu.stanford.nlp.util.logging.Style
 
answerFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
append(CharSequence) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
append(CharSequence, int, int) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
append(char) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
appendHandler(LogRecordHandler, LogRecordHandler) - Static method in class edu.stanford.nlp.util.logging.Redwood
Append a Handler to a portion of the handler tree
appendHandler(Class<? extends LogRecordHandler>, LogRecordHandler) - Static method in class edu.stanford.nlp.util.logging.Redwood
Append a Handler to every parent of the given class
appendHandler(LogRecordHandler) - Static method in class edu.stanford.nlp.util.logging.Redwood
Append a Handler to the end of the root of the Handler tree.
apply(X) - Method in class edu.stanford.nlp.objectbank.IdentityFunction
 
apply(String) - Method in class edu.stanford.nlp.objectbank.ObjectBank.PathToFileFunction
 
apply(Object) - Method in class edu.stanford.nlp.process.Morphology
 
apply(T1) - Method in interface edu.stanford.nlp.util.Function
Converts a T1 to a different T2.
apply() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Apply this configuration to Redwood
apply(Properties) - Static method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Parses a properties file and applies it immediately to Redwood
applyFeatureCountThreshold(List<Pair<Pattern, Integer>>) - Method in class edu.stanford.nlp.classify.Dataset
Applies feature count thresholds to the Dataset.
applyFeatureCountThreshold(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
Applies a feature count threshold to the Dataset.
applyFeatureCountThreshold(int) - Method in class edu.stanford.nlp.classify.RVFDataset
Applies a feature count threshold to the RVFDataset.
applyFeatureMaxCountThreshold(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
Applies a max feature count threshold to the Dataset.
applyFeatureMaxCountThreshold(int) - Method in class edu.stanford.nlp.classify.RVFDataset
Applies a feature max count threshold to the RVFDataset.
applyInitialHessian(double[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
APPROXIMATE - Static variable in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
 
argmax(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmax(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmax(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmax(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Finds and returns the key in the Counter with the largest count.
argmax(Counter<E>, Comparator<E>) - Static method in class edu.stanford.nlp.stats.Counters
Finds and returns the key in the Counter with the largest count.
argmax() - Method in class edu.stanford.nlp.stats.Distribution
 
argmax(Comparator<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the key in this Counter with the largest count.
argmax() - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the key in this Counter with the largest count.
argmax_tieLast(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmin(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmin(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmin(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
argmin(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Finds and returns the key in this Counter with the smallest count.
argmin(Counter<E>, Comparator<E>) - Static method in class edu.stanford.nlp.stats.Counters
Finds and returns the key in this Counter with the smallest count.
argmin(Comparator<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the key in this Counter with the smallest count.
argmin() - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the key in this Counter with the smallest count.
argsToMap(String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Parses command line arguments into a Map.
argsToMap(String[], Map<String, Integer>) - Static method in class edu.stanford.nlp.util.StringUtils
Parses command line arguments into a Map.
argsToProperties(String[]) - Static method in class edu.stanford.nlp.util.StringUtils
In this version each flag has zero or one argument.
argsToProperties(String[], Map<String, Integer>) - Static method in class edu.stanford.nlp.util.StringUtils
Analogous to StringUtils.argsToMap(java.lang.String[]).
ARRAY_LIST_FACTORY - Static variable in class edu.stanford.nlp.util.CollectionFactory
 
ArrayCoreMap - Class in edu.stanford.nlp.util
Base implementation of CoreMap backed by Java Arrays.
ArrayCoreMap() - Constructor for class edu.stanford.nlp.util.ArrayCoreMap
Default constructor - initializes with default initial annotation capacity of 4.
ArrayCoreMap(int) - Constructor for class edu.stanford.nlp.util.ArrayCoreMap
Initializes this ArrayCoreMap, pre-allocating arrays to hold up to capacity key,value pairs.
ArrayCoreMap(ArrayCoreMap) - Constructor for class edu.stanford.nlp.util.ArrayCoreMap
Copy constructor.
ArrayCoreMap(CoreMap) - Constructor for class edu.stanford.nlp.util.ArrayCoreMap
Copy constructor.
ArrayIterable<E> - Class in edu.stanford.nlp.util
 
ArrayIterable(E[]) - Constructor for class edu.stanford.nlp.util.ArrayIterable
 
arrayListFactory() - Static method in class edu.stanford.nlp.util.CollectionFactory
Return a factory for making ArrayList Collections.
arrayListFactory(int) - Static method in class edu.stanford.nlp.util.CollectionFactory
 
ArrayMap<K,V> - Class in edu.stanford.nlp.util
Map backed by an Array.
ArrayMap() - Constructor for class edu.stanford.nlp.util.ArrayMap
 
ArrayMap(int) - Constructor for class edu.stanford.nlp.util.ArrayMap
 
ArrayMap(Map<? extends K, ? extends V>) - Constructor for class edu.stanford.nlp.util.ArrayMap
 
ArrayMap(K[], V[]) - Constructor for class edu.stanford.nlp.util.ArrayMap
 
arrayMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns an ArrayMap.
ArrayMath - Class in edu.stanford.nlp.math
Class ArrayMath
arrayToFile(double[], String) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
ArrayUtils - Class in edu.stanford.nlp.util
Static utility methods for operating on arrays.
ASCENDING_COMPARATOR - Static variable in class edu.stanford.nlp.util.ScoredComparator
 
asCounter(Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
Takes in a Collection of something and makes a counter, incrementing once for each object in the collection.
asCounter(FixedPrioritiesPriorityQueue<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a counter whose keys are the elements in this priority queue, and whose counts are the priorities in this queue.
asFeatures() - Method in class edu.stanford.nlp.ling.BasicDatum
Returns the collection that this BasicDatum was constructed with.
asFeatures() - Method in interface edu.stanford.nlp.ling.Featurizable
returns Object as a Collection of its features
asFeatures() - Method in class edu.stanford.nlp.ling.RVFDatum
Returns the list of features without values
asFeaturesCounter() - Method in class edu.stanford.nlp.ling.RVFDatum
Returns the Counter of features and values
asList(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
needed because Arrays.asList() won't to autoboxing, so if you give it a primitive array you get a singleton list back with just that array as an element.
asList(int[]) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
asList(double[]) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
asList() - Method in class edu.stanford.nlp.util.Pair
 
asList() - Method in class edu.stanford.nlp.util.Triple
 
asMap(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a map view of the given counter.
asPrimitiveDoubleArray(Collection<Double>) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
asPrimitiveIntArray(Collection<Integer>) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
asSet(T[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Return a set containing the same elements as the specified array.
asSet(T[]) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns a new Set containing all the objects in the specified array.
augmentedDateChars - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
auxTrueCaseModels - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
average(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
average(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a new Counter with counts averaged from the two given Counters.
averageCount() - Method in class edu.stanford.nlp.stats.IntCounter
Returns the mean of all the counts (totalCount/size).

B

backgroundSymbol - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
backupFile(File) - Static method in class edu.stanford.nlp.io.IOUtils
 
backupName(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
baseline - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
baseTestDir - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
baseTrainDir - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
BasicDatum<LabelType,FeatureType> - Class in edu.stanford.nlp.ling
Basic implementation of Datum interface that can be constructed with a Collection of features and one more more labels.
BasicDatum(Collection<FeatureType>, Collection<LabelType>) - Constructor for class edu.stanford.nlp.ling.BasicDatum
Constructs a new BasicDatum with the given features and labels.
BasicDatum(Collection<FeatureType>, LabelType) - Constructor for class edu.stanford.nlp.ling.BasicDatum
Constructs a new BasicDatum with the given features and label.
BasicDatum(Collection<FeatureType>) - Constructor for class edu.stanford.nlp.ling.BasicDatum
Constructs a new BasicDatum with the given features and no labels.
BasicDatum() - Constructor for class edu.stanford.nlp.ling.BasicDatum
Constructs a new BasicDatum with no features or labels.
beamSize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
before() - Method in class edu.stanford.nlp.ling.CoreLabel
before() - Method in interface edu.stanford.nlp.ling.HasContext
 
beginPosition() - Method in class edu.stanford.nlp.ling.CoreLabel
 
beginPosition() - Method in interface edu.stanford.nlp.ling.HasOffset
Return the beginning character offset of the label (or -1 if none).
beginPosition() - Method in class edu.stanford.nlp.ling.StringLabel
 
BiasedLogConditionalObjectiveFunction - Class in edu.stanford.nlp.classify
Maximizes the conditional likelihood with a given prior.
BiasedLogConditionalObjectiveFunction(GeneralDataset<?, ?>, double[][]) - Constructor for class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
BiasedLogConditionalObjectiveFunction(GeneralDataset<?, ?>, double[][], LogPrior) - Constructor for class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
BiasedLogConditionalObjectiveFunction(int, int, int[][], int[], double[][]) - Constructor for class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
BiasedLogConditionalObjectiveFunction(int, int, int[][], int[], double[][], LogPrior) - Constructor for class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
BiasedLogisticObjectiveFunction - Class in edu.stanford.nlp.classify
 
BiasedLogisticObjectiveFunction(int, int[][], int[]) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], int[], LogPrior) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], int[], float[]) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], int[], LogPrior, float[]) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], double[][], int[]) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], double[][], int[], LogPrior) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
BiasedLogisticObjectiveFunction(int, int[][], double[][], int[], LogPrior, float[]) - Constructor for class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
biasedTrainFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
BinaryHeapPriorityQueue<E> - Class in edu.stanford.nlp.util
PriorityQueue with explicit double priority values.
BinaryHeapPriorityQueue() - Constructor for class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
BinaryHeapPriorityQueue(int) - Constructor for class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
BinaryHeapPriorityQueue(MapFactory<Object, BinaryHeapPriorityQueue.Entry<E>>) - Constructor for class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
BinaryHeapPriorityQueue(MapFactory<Object, BinaryHeapPriorityQueue.Entry<E>>, int) - Constructor for class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
binnedLengths - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
bioSubmitOutput - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
BLACK - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
BLINK - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
BLUE - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
BOLD - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
booleanFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
box(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
box(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
BROKEN - Static variable in class edu.stanford.nlp.classify.ClassifierExample
 
bSize - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
bSize - Static variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
ByteStreamGobbler - Class in edu.stanford.nlp.util
Stream Gobbler that read and write bytes (can be used to gobble byte based stdout from a process.exec into a file)
ByteStreamGobbler(InputStream, OutputStream) - Constructor for class edu.stanford.nlp.util.ByteStreamGobbler
 
ByteStreamGobbler(String, InputStream, OutputStream) - Constructor for class edu.stanford.nlp.util.ByteStreamGobbler
 
ByteStreamGobbler(String, InputStream, OutputStream, int) - Constructor for class edu.stanford.nlp.util.ByteStreamGobbler
 
byteValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
byteValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
BZip2PipedOutputStream - Class in edu.stanford.nlp.io
Opens a outputstream for writing into a bzip2 file by piping into the bzip2 command.
BZip2PipedOutputStream(String) - Constructor for class edu.stanford.nlp.io.BZip2PipedOutputStream
 
BZip2PipedOutputStream(String, OutputStream) - Constructor for class edu.stanford.nlp.io.BZip2PipedOutputStream
 

C

c - Variable in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
The underlying Collection of input sources.
cacheNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.AdaptedGaussianPriorObjectiveFunction
Calculate the conditional likelihood.
calculate(double[]) - Method in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
Calculate the conditional likelihood.
calculate(double[]) - Method in class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction
 
calculate(double[]) - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
Calculate the value at x and the derivative and save them in the respective fields
calculateRVF(double[]) - Method in class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
calculateRVF(double[]) - Method in class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
calculatesHessianVectorProduct() - Method in enum edu.stanford.nlp.optimization.StochasticCalculateMethods
 
calculateStochastic(double[], double[], int[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
calculateStochastic(double[], double[], int[]) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
calculateStochastic needs to calculate a stochastic approximation to the derivative and value of of a function for a given batch of the data.
calculateStochasticAlgorithmicDifferentiation(double[], double[], int[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
calculateStochasticFiniteDifference(double[], double[], double, int[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
calculateStochasticGradientOnly(double[], int[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
calculateStochasticUpdate(double[], double, int[], double) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
calculateStochasticUpdate(double[], double, int[], double) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffUpdateFunction
Performs stochastic update of weights x (scaled by xscale) based on samples indexed by batch
calculateStochasticUpdate(double[], double, int, double) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffUpdateFunction
Performs stochastic update of weights x (scaled by xscale) based on next batch of batchSize
callingClass - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
callingMethod - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
capitalize(String) - Static method in class edu.stanford.nlp.util.StringUtils
Uppercases the first character of a string.
captureStderr() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Capture stderr and route them through Redwood
captureStdout() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Capture stdout and route them through Redwood
captureStreams() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Capture stdout and stderr and route them through Redwood
captureSystemStreams(boolean, boolean) - Static method in class edu.stanford.nlp.util.logging.Redwood
Captures System.out and System.err and redirects them to Redwood logging.
casedDistSim - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
Whether to (not) lowercase tokens before looking them up in distsim lexicon.
cast(String, Type) - Static method in class edu.stanford.nlp.util.MetaClass
Cast a String representation of an object into that object.
castToInt(double[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
category() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the category value of the label (or null if none).
category() - Method in interface edu.stanford.nlp.ling.HasCategory
Return the category value of the label (or null if none).
CGMinimizer - Class in edu.stanford.nlp.optimization
Conjugate-gradient implementation based on the code in Numerical Recipes in C.
CGMinimizer() - Constructor for class edu.stanford.nlp.optimization.CGMinimizer
Basic constructor, use this.
CGMinimizer(boolean) - Constructor for class edu.stanford.nlp.optimization.CGMinimizer
Pass in false to get per-iteration progress reports (to stderr).
CGMinimizer(Function) - Constructor for class edu.stanford.nlp.optimization.CGMinimizer
Perform minimization with monitoring.
changeFeatureIndex(Index<F>) - Method in class edu.stanford.nlp.classify.Dataset
 
changeLabelIndex(Index<L>) - Method in class edu.stanford.nlp.classify.Dataset
 
changePriority(E, double) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Changes a priority, either up or down, adding the key it if it wasn't there already.
changePriority(E, double) - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Not supported in this implementation.
changePriority(E, double) - Method in interface edu.stanford.nlp.util.PriorityQueue
Changes a priority, either up or down, adding the key it if it wasn't there already.
channelColors - Variable in class edu.stanford.nlp.util.logging.OutputHandler
 
channels(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Create an object representing a group of channels.
channels() - Method in class edu.stanford.nlp.util.logging.Redwood.Record
Returns the channels for this record, in sorted order (special channels first, then alphabetical)
channels(Object...) - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
Creates a new RedwoodChannels object, concatenating the channels from this RedwoodChannels with some additional channels.
channelSeparatorChar - Variable in class edu.stanford.nlp.util.logging.OutputHandler
Character used to join multiple channel names
channelStyles - Variable in class edu.stanford.nlp.util.logging.OutputHandler
 
charHalfWindow - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
checkConstructor(Object...) - Method in class edu.stanford.nlp.util.MetaClass
 
checkError() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
checkFlagExclusiveSet(int, int, int) - Static method in class edu.stanford.nlp.util.Interval
Utility function to check if a particular flag is set exclusively given a particular set of flags and a mask
checkFlagSet(int, int) - Static method in class edu.stanford.nlp.util.Interval
Utility function to check if a particular flag is set given a particular set of flags
checkMultipleBitSet(int) - Static method in class edu.stanford.nlp.util.Interval
Utility function to check if multiple bits are set for flags
checkNameList - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
checkRequiredProperties(Properties, String...) - Static method in class edu.stanford.nlp.util.StringUtils
If any of the given list of properties are not found, returns the name of that property.
children() - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
chiSquare2by2(int, int, int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Find a 2x2 chi-square value.
chomp(String) - Static method in class edu.stanford.nlp.util.StringUtils
Returns the supplied string with any trailing '\n' removed.
chomp(Object) - Static method in class edu.stanford.nlp.util.StringUtils
Returns the result of calling toString() on the supplied Object, but with any trailing '\n' removed.
CL - Static variable in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
classBias - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ClassicCounter<E> - Class in edu.stanford.nlp.stats
A specialized kind of hash table (or map) for storing numeric counts for objects.
ClassicCounter() - Constructor for class edu.stanford.nlp.stats.ClassicCounter
Constructs a new (empty) Counter backed by a HashMap.
ClassicCounter(MapFactory<E, MutableDouble>) - Constructor for class edu.stanford.nlp.stats.ClassicCounter
Pass in a MapFactory and the map it vends will back your Counter.
ClassicCounter(MapFactory<E, MutableDouble>, int) - Constructor for class edu.stanford.nlp.stats.ClassicCounter
Pass in a MapFactory and the map it vends will back your Counter.
ClassicCounter(Counter<E>) - Constructor for class edu.stanford.nlp.stats.ClassicCounter
Constructs a new Counter with the contents of the given Counter.
ClassicCounter(Collection<E>) - Constructor for class edu.stanford.nlp.stats.ClassicCounter
Constructs a new Counter by counting the elements in the given Collection.
Classifier<L,F> - Interface in edu.stanford.nlp.classify
A simple interface for classifying and scoring data points, implemented by most of the classifiers in this package.
ClassifierCreator<L,F> - Interface in edu.stanford.nlp.classify
Creates a classifier with given weights
ClassifierExample - Class in edu.stanford.nlp.classify
Sample code that illustrates the training and use of a linear classifier.
ClassifierFactory<L,F,C extends Classifier<L,F>> - Interface in edu.stanford.nlp.classify
A simple interface for training a Classifier from a Dataset of training examples.
classifierType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
classOf(Datum<L, F>) - Method in interface edu.stanford.nlp.classify.Classifier
 
classOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
classOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
classOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
classOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
classOf(Counter<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
classOf(Collection<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
classOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
classOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
classOf(RVFDatum<L, F>) - Method in interface edu.stanford.nlp.classify.RVFClassifier
 
clean() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
cleanGazette - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
clear() - Method in class edu.stanford.nlp.classify.GeneralDataset
Resets the Dataset so that it is empty and ready to collect data.
clear(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
Resets the Dataset so that it is empty and ready to collect data.
clear() - Method in class edu.stanford.nlp.classify.RVFDataset
Resets the Dataset so that it is empty and ready to collect data.
clear(int) - Method in class edu.stanford.nlp.classify.RVFDataset
Resets the Dataset so that it is empty and ready to collect data.
clear() - Method in class edu.stanford.nlp.objectbank.ObjectBank
 
clear() - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
clear() - Method in class edu.stanford.nlp.stats.ClassicCounter
Removes all entries from the counter.
clear() - Method in interface edu.stanford.nlp.stats.Counter
Removes all entries from the counter.
clear() - Method in class edu.stanford.nlp.stats.IntCounter
Removes all counts from this Counter.
clear() - Method in class edu.stanford.nlp.util.ArrayMap
 
clear() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Clears the queue.
clear() - Method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
clear() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
clear() - Method in class edu.stanford.nlp.util.HashIndex
Clears this Index.
clear() - Method in interface edu.stanford.nlp.util.Index
 
clear() - Method in class edu.stanford.nlp.util.Interner
 
clear() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Clear any custom configurations to Redwood
clearCache() - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
Clears the cache in a way that doesn't require reallocation :-)
clearCache() - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
Clears the cache in a way that doesn't require reallocation :-)
clearError() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
clearHandlers() - Static method in class edu.stanford.nlp.util.logging.Redwood
Remove all log handlers from Redwood, presumably in order to construct a custom pipeline afterwards
clearLoggingClasses() - Static method in class edu.stanford.nlp.util.logging.Redwood
Removes all classes from the list of known logging classes
clearMemory() - Method in class edu.stanford.nlp.objectbank.ObjectBank
If you are keeping the contents in memory, this will clear hte memory, and they will be recomputed the next time iterator() is called.
clone() - Method in class edu.stanford.nlp.stats.IntCounter
 
clone() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns a clone of this priority queue.
close() - Method in class edu.stanford.nlp.io.BZip2PipedOutputStream
 
close() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
closeIgnoringExceptions(Closeable) - Static method in class edu.stanford.nlp.io.IOUtils
Provides an implementation of closing a file for use in a finally block so you can correctly close a file without even more exception handling stuff.
collapseApproximate() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Collapse repeated records, using an approximate notion of equality (i.e.
collapseExact() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Collapse repeated records, using exact string match on the record.
collapseNN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
collapseNone() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Do not collapse repeated records
CollectionFactory<T> - Class in edu.stanford.nlp.util
Factory for vending Collections.
CollectionFactory() - Constructor for class edu.stanford.nlp.util.CollectionFactory
 
CollectionFactory.ArrayListFactory<T> - Class in edu.stanford.nlp.util
 
CollectionFactory.ArrayListFactory() - Constructor for class edu.stanford.nlp.util.CollectionFactory.ArrayListFactory
 
CollectionFactory.HashSetFactory<T> - Class in edu.stanford.nlp.util
 
CollectionFactory.HashSetFactory() - Constructor for class edu.stanford.nlp.util.CollectionFactory.HashSetFactory
 
CollectionFactory.LinkedListFactory<T> - Class in edu.stanford.nlp.util
 
CollectionFactory.LinkedListFactory() - Constructor for class edu.stanford.nlp.util.CollectionFactory.LinkedListFactory
 
CollectionFactory.SizedArrayListFactory<T> - Class in edu.stanford.nlp.util
 
CollectionFactory.SizedArrayListFactory(int) - Constructor for class edu.stanford.nlp.util.CollectionFactory.SizedArrayListFactory
 
CollectionFactory.TreeSetFactory<T> - Class in edu.stanford.nlp.util
 
CollectionFactory.TreeSetFactory() - Constructor for class edu.stanford.nlp.util.CollectionFactory.TreeSetFactory
 
CollectionUtils - Class in edu.stanford.nlp.util
Collection of useful static methods for working with Collections.
Color - Enum in edu.stanford.nlp.util.logging
ANSI supported colors These values are mirrored in Redwood.Util
colorChannel(String, Color) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Color the tag for a particular channel this color
ColumnDataClassifier - Class in edu.stanford.nlp.classify
ColumnDataClassifier provides a command-line interface for doing context-free (independent) classification of a series of data items, where each data item is represented by a line of a file, as a list of String variables, in tab-separated columns.
ColumnDataClassifier(String) - Constructor for class edu.stanford.nlp.classify.ColumnDataClassifier
Construct a ColumnDataClassifier.
ColumnDataClassifier(Properties) - Constructor for class edu.stanford.nlp.classify.ColumnDataClassifier
Construct a ColumnDataClassifier.
columnStringToObject(Class, String, String, String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Converts a tab delimited string into an object with given fields Requires the object has setXxx functions for the specified fields
columnStringToObject(Class<?>, String, Pattern, String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Converts a tab delimited string into an object with given fields Requires the object has public access for the specified fields
combo - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
comboProps - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
compact() - Method in class edu.stanford.nlp.util.ArrayCoreMap
Reduces memory consumption to the minimum for representing the values currently stored stored in this object.
compare(Scored, Scored) - Method in class edu.stanford.nlp.util.ScoredComparator
 
compareArrays(T[], T[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Provides a consistent ordering over arrays.
compareIntervalOrder(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Returns order of another interval compared to this one
compareLists(List<T>, List<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Provides a consistent ordering over lists.
compareTo(ValueLabel) - Method in class edu.stanford.nlp.ling.ValueLabel
Orders by value()'s lexicographic ordering.
compareTo(WordLemmaTag) - Method in class edu.stanford.nlp.ling.WordLemmaTag
Orders first by word, then by lemma, then by tag.
compareTo(WordTag) - Method in class edu.stanford.nlp.ling.WordTag
Orders first by word, then by tag.
compareTo(IntTuple) - Method in class edu.stanford.nlp.util.IntTuple
 
compareTo(MutableDouble) - Method in class edu.stanford.nlp.util.MutableDouble
Compares two MutableDouble objects numerically.
compareTo(MutableInteger) - Method in class edu.stanford.nlp.util.MutableInteger
Compares two MutableInteger objects numerically.
compareTo(Pair<T1, T2>) - Method in class edu.stanford.nlp.util.Pair
Compares this Pair to another object.
compute(double[], double[]) - Method in class edu.stanford.nlp.classify.LogPrior
Adjust the given grad array by adding the prior's gradient component and return the value of the logPrior
computeAverage(Function<Triple<GeneralDataset<L, F>, GeneralDataset<L, F>, CrossValidator.SavedState>, Double>) - Method in class edu.stanford.nlp.classify.CrossValidator
This computes the average over all folds of the function we're trying to optimize.
computeStochastic(double[], double[], double) - Method in class edu.stanford.nlp.classify.LogPrior
 
concat(IntTuple, IntTuple) - Static method in class edu.stanford.nlp.util.IntTuple
 
confidenceWeightedAccuracy() - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
confusionMatrix - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
conjoinShapeNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
console() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a console pipeline to the Redwood handler tree, Calling this multiple times will result in messages being printed multiple times.
contains(int[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
contains(Object) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Can be slow.
contains(T[], T) - Static method in class edu.stanford.nlp.util.ArrayUtils
Returns true iff object o equals (not ==) some element of array a.
contains(Object) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Returns whether the queue contains the given key.
contains(Object) - Method in class edu.stanford.nlp.util.HashIndex
Checks whether an Object already has an index in the Index
contains(Object) - Method in interface edu.stanford.nlp.util.Index
 
contains(E) - Method in class edu.stanford.nlp.util.Interval
Checks whether the point p is contained inside this interval
containsAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Can be slow.
containsAny(Collection<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
if any item in toCheck is present in collection
containsIgnoreCase(Collection<String>, String) - Static method in class edu.stanford.nlp.util.StringUtils
Convenience method: a case-insensitive variant of Collection.contains
containsInSubarray(int[], int, int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
containsKey(E) - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns whether a Counter contains a key.
containsKey(E) - Method in interface edu.stanford.nlp.stats.Counter
Returns whether a Counter contains a key.
containsKey(E) - Method in class edu.stanford.nlp.stats.Distribution
 
containsKey(E) - Method in class edu.stanford.nlp.stats.IntCounter
 
containsKey(K1, K2) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
containsKey(K1, K2) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
containsKey(Class<KEY>) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Returns true if contains the given key.
containsKey(Class<KEY>) - Method in interface edu.stanford.nlp.util.TypesafeMap
Returns true if contains the given key.
containsObject(Collection<T>, T) - Static method in class edu.stanford.nlp.util.CollectionUtils
Checks whether a Collection contains a specified Object.
content - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
copy(double[], double[]) - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
copy(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(int[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(double[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(double[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(double[][][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(float[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(float[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copy(float[][][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
copyOf(double[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
Simulate Arrays.copyOf method provided by Java 6 When/if the JavaNLP-core code base moves past Java 5, this method can be removed
CoreAnnotation<V> - Interface in edu.stanford.nlp.ling
The base class for any annotation that can be marked on a CoreMap, parameterized by the type of the value associated with the annotation.
CoreAnnotations - Class in edu.stanford.nlp.ling
Set of common annotations for CoreMaps.
CoreAnnotations.AbbrAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.AbbrAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AbbrAnnotation
 
CoreAnnotations.AbgeneAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.AbgeneAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AbgeneAnnotation
 
CoreAnnotations.AbstrAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.AbstrAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AbstrAnnotation
 
CoreAnnotations.AfterAnnotation - Class in edu.stanford.nlp.ling
Annotation for the whitespace characters appear after this word.
CoreAnnotations.AfterAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AfterAnnotation
 
CoreAnnotations.AnswerAnnotation - Class in edu.stanford.nlp.ling
The standard key for the answer which is a String
CoreAnnotations.AnswerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AnswerAnnotation
 
CoreAnnotations.AnswerObjectAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.AnswerObjectAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AnswerObjectAnnotation
 
CoreAnnotations.AntecedentAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the annotation's antecedent.
CoreAnnotations.AntecedentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.AntecedentAnnotation
 
CoreAnnotations.ArgDescendentAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ArgDescendentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ArgDescendentAnnotation
 
CoreAnnotations.ArgumentAnnotation - Class in edu.stanford.nlp.ling
The standard key for a propbank label which is of type Argument
CoreAnnotations.ArgumentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ArgumentAnnotation
 
CoreAnnotations.BagOfWordsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.BagOfWordsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BagOfWordsAnnotation
 
CoreAnnotations.BeAnnotation - Class in edu.stanford.nlp.ling
annotation stolen from the lex parser
CoreAnnotations.BeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BeAnnotation
 
CoreAnnotations.BeforeAnnotation - Class in edu.stanford.nlp.ling
Annotation for the whitespace characters appearing before this word.
CoreAnnotations.BeforeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BeforeAnnotation
 
CoreAnnotations.BeginIndexAnnotation - Class in edu.stanford.nlp.ling
This indexes the beginning of a span of words, e.g., a constituent in a tree.
CoreAnnotations.BeginIndexAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BeginIndexAnnotation
 
CoreAnnotations.BestCliquesAnnotation - Class in edu.stanford.nlp.ling
Used in Task3 Pascal system
CoreAnnotations.BestCliquesAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BestCliquesAnnotation
 
CoreAnnotations.BestFullAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.BestFullAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.BestFullAnnotation
 
CoreAnnotations.CalendarAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the date and time associated with an annotation.
CoreAnnotations.CalendarAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CalendarAnnotation
 
CoreAnnotations.CategoryAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.CategoryAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CategoryAnnotation
 
CoreAnnotations.CategoryFunctionalTagAnnotation - Class in edu.stanford.nlp.ling
The standard key for storing category with functional tags.
CoreAnnotations.CategoryFunctionalTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CategoryFunctionalTagAnnotation
 
CoreAnnotations.CharacterOffsetBeginAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the offset of the first character of an annotation.
CoreAnnotations.CharacterOffsetBeginAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CharacterOffsetBeginAnnotation
 
CoreAnnotations.CharacterOffsetEndAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the offset of the last character after the end of an annotation.
CoreAnnotations.CharacterOffsetEndAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CharacterOffsetEndAnnotation
 
CoreAnnotations.CharAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.CharAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CharAnnotation
 
CoreAnnotations.ChineseCharAnnotation - Class in edu.stanford.nlp.ling
for Chinese: character level information, segmentation
CoreAnnotations.ChineseCharAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ChineseCharAnnotation
 
CoreAnnotations.ChineseIsSegmentedAnnotation - Class in edu.stanford.nlp.ling
Not sure exactly what this is, but it is different from ChineseSegAnnotation and seems to indicate if the text is segmented
CoreAnnotations.ChineseIsSegmentedAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ChineseIsSegmentedAnnotation
 
CoreAnnotations.ChineseOrigSegAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ChineseOrigSegAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ChineseOrigSegAnnotation
 
CoreAnnotations.ChineseSegAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ChineseSegAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ChineseSegAnnotation
 
CoreAnnotations.ChunkAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ChunkAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ChunkAnnotation
 
CoreAnnotations.CoarseTagAnnotation - Class in edu.stanford.nlp.ling
CoNLL dep parsing - coarser POS tags.
CoreAnnotations.CoarseTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoarseTagAnnotation
 
CoreAnnotations.CommonWordsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.CommonWordsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CommonWordsAnnotation
 
CoreAnnotations.CoNLLDepAnnotation - Class in edu.stanford.nlp.ling
CoNLL dep parsing - the dependency type
CoreAnnotations.CoNLLDepAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepAnnotation
 
CoreAnnotations.CoNLLDepParentIndexAnnotation - Class in edu.stanford.nlp.ling
CoNLL dep parsing - the index of the word which is the parent of this word in the dependency tree
CoreAnnotations.CoNLLDepParentIndexAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepParentIndexAnnotation
 
CoreAnnotations.CoNLLDepTypeAnnotation - Class in edu.stanford.nlp.ling
CoNLL dep parsing - the dependency type
CoreAnnotations.CoNLLDepTypeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepTypeAnnotation
 
CoreAnnotations.CoNLLPredicateAnnotation - Class in edu.stanford.nlp.ling
CoNLL SRL/dep parsing - whether the word is a predicate
CoreAnnotations.CoNLLPredicateAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoNLLPredicateAnnotation
 
CoreAnnotations.CoNLLSRLAnnotation - Class in edu.stanford.nlp.ling
CoNLL SRL/dep parsing - map which, for the current word, specifies its specific role for each predicate
CoreAnnotations.CoNLLSRLAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CoNLLSRLAnnotation
 
CoreAnnotations.ContextsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ContextsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ContextsAnnotation
 
CoreAnnotations.CopyAnnotation - Class in edu.stanford.nlp.ling
Used in nlp.trees.
CoreAnnotations.CopyAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CopyAnnotation
 
CoreAnnotations.CostMagnificationAnnotation - Class in edu.stanford.nlp.ling
Key for relative value of a word - used in RTE
CoreAnnotations.CostMagnificationAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CostMagnificationAnnotation
 
CoreAnnotations.CovertIDAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.CovertIDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.CovertIDAnnotation
 
CoreAnnotations.D2_LBeginAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.D2_LBeginAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.D2_LBeginAnnotation
 
CoreAnnotations.D2_LEndAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.D2_LEndAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.D2_LEndAnnotation
 
CoreAnnotations.D2_LMiddleAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.D2_LMiddleAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.D2_LMiddleAnnotation
 
CoreAnnotations.DayAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.DayAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DayAnnotation
 
CoreAnnotations.DependentsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.DependentsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DependentsAnnotation
 
CoreAnnotations.DictAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.DictAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DictAnnotation
 
CoreAnnotations.DistSimAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.DistSimAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DistSimAnnotation
 
CoreAnnotations.DoAnnotation - Class in edu.stanford.nlp.ling
annotation stolen from the lex parser
CoreAnnotations.DoAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DoAnnotation
 
CoreAnnotations.DocDateAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.DocDateAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DocDateAnnotation
 
CoreAnnotations.DocIDAnnotation - Class in edu.stanford.nlp.ling
This refers to the unique identifier for a "document", where document may vary based on your application.
CoreAnnotations.DocIDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DocIDAnnotation
 
CoreAnnotations.DomainAnnotation - Class in edu.stanford.nlp.ling
Used in CRFClassifier stuff PositionAnnotation should possibly be an int - it's present as either an int or string depending on context CharAnnotation may be "CharacterAnnotation" - not sure
CoreAnnotations.DomainAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.DomainAnnotation
 
CoreAnnotations.EndIndexAnnotation - Class in edu.stanford.nlp.ling
This indexes the end of a span of words, e.g., a constituent in a tree.
CoreAnnotations.EndIndexAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.EndIndexAnnotation
 
CoreAnnotations.EntityClassAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.EntityClassAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.EntityClassAnnotation
 
CoreAnnotations.EntityRuleAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.EntityRuleAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.EntityRuleAnnotation
 
CoreAnnotations.EntityTypeAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.EntityTypeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.EntityTypeAnnotation
 
CoreAnnotations.FeaturesAnnotation - Class in edu.stanford.nlp.ling
The standard key for the features which is a Collection
CoreAnnotations.FeaturesAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.FeaturesAnnotation
 
CoreAnnotations.FemaleGazAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.FemaleGazAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.FemaleGazAnnotation
 
CoreAnnotations.FirstChildAnnotation - Class in edu.stanford.nlp.ling
used in binarized trees to specify the first child in the rule for which this node is the parent
CoreAnnotations.FirstChildAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.FirstChildAnnotation
 
CoreAnnotations.ForcedSentenceEndAnnotation - Class in edu.stanford.nlp.ling
This indicates the sentence should end at this token.
CoreAnnotations.ForcedSentenceEndAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ForcedSentenceEndAnnotation
 
CoreAnnotations.FreqAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.FreqAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.FreqAnnotation
 
CoreAnnotations.GazAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.GazAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GazAnnotation
 
CoreAnnotations.GazetteerAnnotation - Class in edu.stanford.nlp.ling
The standard key for the gazetteer information
CoreAnnotations.GazetteerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GazetteerAnnotation
 
CoreAnnotations.GenericTokensAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the tokens (can be words, phrases or anything that are of type CoreMap) contained by an annotation.
CoreAnnotations.GenericTokensAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GenericTokensAnnotation
 
CoreAnnotations.GeniaAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.GeniaAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GeniaAnnotation
 
CoreAnnotations.GoldAnswerAnnotation - Class in edu.stanford.nlp.ling
The standard key for gold answer which is a String
CoreAnnotations.GoldAnswerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GoldAnswerAnnotation
 
CoreAnnotations.GovernorAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.GovernorAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GovernorAnnotation
 
CoreAnnotations.GrandparentAnnotation - Class in edu.stanford.nlp.ling
specifies the base state of the parent of this node in the parse tree
CoreAnnotations.GrandparentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.GrandparentAnnotation
 
CoreAnnotations.HaveAnnotation - Class in edu.stanford.nlp.ling
annotation stolen from the lex parser
CoreAnnotations.HaveAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.HaveAnnotation
 
CoreAnnotations.HeadWordStringAnnotation - Class in edu.stanford.nlp.ling
The key for storing a Head word as a string rather than a pointer (as in TreeCoreAnnotations.HeadWordAnnotation)
CoreAnnotations.HeadWordStringAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.HeadWordStringAnnotation
 
CoreAnnotations.HeightAnnotation - Class in edu.stanford.nlp.ling
Used in srl.unsup
CoreAnnotations.HeightAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.HeightAnnotation
 
CoreAnnotations.IDAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.IDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.IDAnnotation
 
CoreAnnotations.IDFAnnotation - Class in edu.stanford.nlp.ling
Inverse document frequency of the word this label represents
CoreAnnotations.IDFAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.IDFAnnotation
 
CoreAnnotations.INAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.INAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.INAnnotation
 
CoreAnnotations.IndexAnnotation - Class in edu.stanford.nlp.ling
This indexes a token number inside a sentence.
CoreAnnotations.IndexAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.IndexAnnotation
 
CoreAnnotations.InterpretationAnnotation - Class in edu.stanford.nlp.ling
The standard key for the semantic interpretation
CoreAnnotations.InterpretationAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.InterpretationAnnotation
 
CoreAnnotations.IsDateRangeAnnotation - Class in edu.stanford.nlp.ling
it really seems like this should have a different name or else be a boolean
CoreAnnotations.IsDateRangeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.IsDateRangeAnnotation
 
CoreAnnotations.IsURLAnnotation - Class in edu.stanford.nlp.ling
it really seems like this should have a different name or else be a boolean
CoreAnnotations.IsURLAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.IsURLAnnotation
 
CoreAnnotations.LabelAnnotation - Class in edu.stanford.nlp.ling
Used in wsd.supwsd package
CoreAnnotations.LabelAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LabelAnnotation
 
CoreAnnotations.LabelWeightAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LabelWeightAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LabelWeightAnnotation
 
CoreAnnotations.LastGazAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LastGazAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LastGazAnnotation
 
CoreAnnotations.LastTaggedAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LastTaggedAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LastTaggedAnnotation
 
CoreAnnotations.LBeginAnnotation - Class in edu.stanford.nlp.ling
Used in Gale2007ChineseSegmenter
CoreAnnotations.LBeginAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LBeginAnnotation
 
CoreAnnotations.LeftChildrenNodeAnnotation - Class in edu.stanford.nlp.ling
used in incremental DAG parser
CoreAnnotations.LeftChildrenNodeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LeftChildrenNodeAnnotation
 
CoreAnnotations.LeftTermAnnotation - Class in edu.stanford.nlp.ling
The Standard key for storing the left terminal number relative to the root of the tree of the leftmost terminal dominated by the current node
CoreAnnotations.LeftTermAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LeftTermAnnotation
 
CoreAnnotations.LemmaAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the lemma (morphological stem) of a token.
CoreAnnotations.LemmaAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LemmaAnnotation
 
CoreAnnotations.LEndAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LEndAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LEndAnnotation
 
CoreAnnotations.LengthAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LengthAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LengthAnnotation
 
CoreAnnotations.LMiddleAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.LMiddleAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.LMiddleAnnotation
 
CoreAnnotations.MaleGazAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.MaleGazAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MaleGazAnnotation
 
CoreAnnotations.MarkingAnnotation - Class in edu.stanford.nlp.ling
Another key used for propbank - to signify core arg nodes or predicate nodes
CoreAnnotations.MarkingAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MarkingAnnotation
 
CoreAnnotations.MonthAnnotation - Class in edu.stanford.nlp.ling
Used in nlp.coref
CoreAnnotations.MonthAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MonthAnnotation
 
CoreAnnotations.MorphoCaseAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.MorphoCaseAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MorphoCaseAnnotation
 
CoreAnnotations.MorphoGenAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.MorphoGenAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MorphoGenAnnotation
 
CoreAnnotations.MorphoNumAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.MorphoNumAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MorphoNumAnnotation
 
CoreAnnotations.MorphoPersAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.MorphoPersAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.MorphoPersAnnotation
 
CoreAnnotations.NamedEntityTagAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the token-level named entity tag (e.g., DATE, PERSON, etc.) This key is typically set on token annotations.
CoreAnnotations.NamedEntityTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NamedEntityTagAnnotation
 
CoreAnnotations.NeighborsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NeighborsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NeighborsAnnotation
 
CoreAnnotations.NERIDAnnotation - Class in edu.stanford.nlp.ling
This is an NER ID annotation (in case the all caps parsing didn't work out for you...)
CoreAnnotations.NERIDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NERIDAnnotation
 
CoreAnnotations.NormalizedNamedEntityTagAnnotation - Class in edu.stanford.nlp.ling
The key for the normalized value of numeric named entities.
CoreAnnotations.NormalizedNamedEntityTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NormalizedNamedEntityTagAnnotation
 
CoreAnnotations.NotAnnotation - Class in edu.stanford.nlp.ling
annotation stolen from the lex parser
CoreAnnotations.NotAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NotAnnotation
 
CoreAnnotations.NumericCompositeObjectAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericCompositeObjectAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeObjectAnnotation
 
CoreAnnotations.NumericCompositeTypeAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericCompositeTypeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeTypeAnnotation
 
CoreAnnotations.NumericCompositeValueAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericCompositeValueAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeValueAnnotation
 
CoreAnnotations.NumericObjectAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericObjectAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericObjectAnnotation
 
CoreAnnotations.NumericTypeAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericTypeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericTypeAnnotation
 
CoreAnnotations.NumericValueAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumericValueAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumericValueAnnotation
 
CoreAnnotations.NumerizedTokensAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.NumerizedTokensAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumerizedTokensAnnotation
 
CoreAnnotations.NumTxtSentencesAnnotation - Class in edu.stanford.nlp.ling
Used by RTE to track number of text sentences, to determine when hyp sentences begin.
CoreAnnotations.NumTxtSentencesAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.NumTxtSentencesAnnotation
 
CoreAnnotations.OriginalAnswerAnnotation - Class in edu.stanford.nlp.ling
Seems like this could be consolidated with something else...
CoreAnnotations.OriginalAnswerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.OriginalAnswerAnnotation
 
CoreAnnotations.OriginalCharAnnotation - Class in edu.stanford.nlp.ling
Seems like this could be consolidated with something else...
CoreAnnotations.OriginalCharAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.OriginalCharAnnotation
 
CoreAnnotations.OriginalTextAnnotation - Class in edu.stanford.nlp.ling
The exact original surface form of a token.
CoreAnnotations.OriginalTextAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.OriginalTextAnnotation
 
CoreAnnotations.ParagraphAnnotation - Class in edu.stanford.nlp.ling
used in dcoref.
CoreAnnotations.ParagraphAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ParagraphAnnotation
 
CoreAnnotations.ParagraphsAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the paragraphs contained by an annotation.
CoreAnnotations.ParagraphsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ParagraphsAnnotation
 
CoreAnnotations.ParaPositionAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ParaPositionAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ParaPositionAnnotation
 
CoreAnnotations.ParentAnnotation - Class in edu.stanford.nlp.ling
The standard key for the parent which is a String
CoreAnnotations.ParentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ParentAnnotation
 
CoreAnnotations.PartOfSpeechAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the Penn part of speech of a token.
CoreAnnotations.PartOfSpeechAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PartOfSpeechAnnotation
 
CoreAnnotations.PercentAnnotation - Class in edu.stanford.nlp.ling
annotation stolen from the lex parser
CoreAnnotations.PercentAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PercentAnnotation
 
CoreAnnotations.PhraseWordsAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PhraseWordsAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PhraseWordsAnnotation
 
CoreAnnotations.PhraseWordsTagAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PhraseWordsTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PhraseWordsTagAnnotation
 
CoreAnnotations.PolarityAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PolarityAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PolarityAnnotation
 
CoreAnnotations.PositionAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PositionAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PositionAnnotation
 
CoreAnnotations.PossibleAnswersAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PossibleAnswersAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PossibleAnswersAnnotation
 
CoreAnnotations.PredictedAnswerAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.PredictedAnswerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PredictedAnswerAnnotation
 
CoreAnnotations.PrevChildAnnotation - Class in edu.stanford.nlp.ling
used in binarized trees to say the name of the most recent child
CoreAnnotations.PrevChildAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PrevChildAnnotation
 
CoreAnnotations.PriorAnnotation - Class in edu.stanford.nlp.ling
Used in propbank.srl
CoreAnnotations.PriorAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.PriorAnnotation
 
CoreAnnotations.ProjectedCategoryAnnotation - Class in edu.stanford.nlp.ling
The standard key for storing a projected category in the map, as a String.
CoreAnnotations.ProjectedCategoryAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ProjectedCategoryAnnotation
 
CoreAnnotations.ProtoAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.ProtoAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ProtoAnnotation
 
CoreAnnotations.RoleAnnotation - Class in edu.stanford.nlp.ling
The standard key for the semantic role label of a phrase.
CoreAnnotations.RoleAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.RoleAnnotation
 
CoreAnnotations.SectionAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SectionAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SectionAnnotation
 
CoreAnnotations.SemanticHeadTagAnnotation - Class in edu.stanford.nlp.ling
The standard key for Semantic Head Word POS which is a String
CoreAnnotations.SemanticHeadTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SemanticHeadTagAnnotation
 
CoreAnnotations.SemanticHeadWordAnnotation - Class in edu.stanford.nlp.ling
The standard key for Semantic Head Word which is a String
CoreAnnotations.SemanticHeadWordAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SemanticHeadWordAnnotation
 
CoreAnnotations.SemanticTagAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SemanticTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SemanticTagAnnotation
 
CoreAnnotations.SemanticWordAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SemanticWordAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SemanticWordAnnotation
 
CoreAnnotations.SentenceIDAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SentenceIDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SentenceIDAnnotation
 
CoreAnnotations.SentenceIndexAnnotation - Class in edu.stanford.nlp.ling
Unique identifier within a document for a given sentence.
CoreAnnotations.SentenceIndexAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SentenceIndexAnnotation
 
CoreAnnotations.SentencePositionAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SentencePositionAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SentencePositionAnnotation
 
CoreAnnotations.SentencesAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the sentences contained by an annotation.
CoreAnnotations.SentencesAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SentencesAnnotation
 
CoreAnnotations.ShapeAnnotation - Class in edu.stanford.nlp.ling
The standard key for the "shape" of a word: a String representing the type of characters in a word, such as "Xx" for a capitalized word.
CoreAnnotations.ShapeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ShapeAnnotation
 
CoreAnnotations.SpaceBeforeAnnotation - Class in edu.stanford.nlp.ling
Used in Chinese segmenters for whether there was space before a character.
CoreAnnotations.SpaceBeforeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SpaceBeforeAnnotation
 
CoreAnnotations.SpanAnnotation - Class in edu.stanford.nlp.ling
The standard key for span which is an IntPair
CoreAnnotations.SpanAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SpanAnnotation
 
CoreAnnotations.SpeakerAnnotation - Class in edu.stanford.nlp.ling
used in dcoref.
CoreAnnotations.SpeakerAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SpeakerAnnotation
 
CoreAnnotations.SRL_ID - Enum in edu.stanford.nlp.ling
 
CoreAnnotations.SRLIDAnnotation - Class in edu.stanford.nlp.ling
The key for semantic role labels (Note: please add to this description if you use this key)
CoreAnnotations.SRLIDAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SRLIDAnnotation
 
CoreAnnotations.SRLInstancesAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SRLInstancesAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SRLInstancesAnnotation
 
CoreAnnotations.StackedNamedEntityTagAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the token-level named entity tag (e.g., DATE, PERSON, etc.) from a previous NER tagger.
CoreAnnotations.StackedNamedEntityTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.StackedNamedEntityTagAnnotation
 
CoreAnnotations.StateAnnotation - Class in edu.stanford.nlp.ling
The base version of the parser state, like NP or VBZ or ...
CoreAnnotations.StateAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.StateAnnotation
 
CoreAnnotations.StemAnnotation - Class in edu.stanford.nlp.ling
Morphological stem of the word this label represents
CoreAnnotations.StemAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.StemAnnotation
 
CoreAnnotations.SubcategorizationAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.SubcategorizationAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.SubcategorizationAnnotation
 
CoreAnnotations.TagLabelAnnotation - Class in edu.stanford.nlp.ling
Used in Trees
CoreAnnotations.TagLabelAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TagLabelAnnotation
 
CoreAnnotations.TextAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the annotation's text.
CoreAnnotations.TextAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TextAnnotation
 
CoreAnnotations.TokenBeginAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the first token included in an annotation.
CoreAnnotations.TokenBeginAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TokenBeginAnnotation
 
CoreAnnotations.TokenEndAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the last token after the end of an annotation.
CoreAnnotations.TokenEndAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TokenEndAnnotation
 
CoreAnnotations.TokensAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the tokens contained by an annotation.
CoreAnnotations.TokensAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TokensAnnotation
 
CoreAnnotations.TopicAnnotation - Class in edu.stanford.nlp.ling
Used for Topic Assignments from LDA or its equivalent models.
CoreAnnotations.TopicAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TopicAnnotation
 
CoreAnnotations.TrueCaseAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key for getting the token-level true case annotation (e.g., INIT_UPPER) This key is typically set on token annotations.
CoreAnnotations.TrueCaseAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TrueCaseAnnotation
 
CoreAnnotations.TrueCaseTextAnnotation - Class in edu.stanford.nlp.ling
The CoreMap key identifying the annotation's true-cased text.
CoreAnnotations.TrueCaseTextAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TrueCaseTextAnnotation
 
CoreAnnotations.TrueTagAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.TrueTagAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.TrueTagAnnotation
 
CoreAnnotations.UBlockAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.UBlockAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.UBlockAnnotation
 
CoreAnnotations.UnaryAnnotation - Class in edu.stanford.nlp.ling
whether the node is the parent in a unary rule
CoreAnnotations.UnaryAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.UnaryAnnotation
 
CoreAnnotations.UnknownAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.UnknownAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.UnknownAnnotation
 
CoreAnnotations.UtteranceAnnotation - Class in edu.stanford.nlp.ling
used in dcoref.
CoreAnnotations.UtteranceAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.UtteranceAnnotation
 
CoreAnnotations.UTypeAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.UTypeAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.UTypeAnnotation
 
CoreAnnotations.ValueAnnotation - Class in edu.stanford.nlp.ling
Contains the "value" - an ill-defined string used widely in MapLabel.
CoreAnnotations.ValueAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.ValueAnnotation
 
CoreAnnotations.VerbSenseAnnotation - Class in edu.stanford.nlp.ling
Probank key for the Verb sense given in the Propbank Annotation, should only be in the verbnode
CoreAnnotations.VerbSenseAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.VerbSenseAnnotation
 
CoreAnnotations.WebAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.WebAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.WebAnnotation
 
CoreAnnotations.WordFormAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.WordFormAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.WordFormAnnotation
 
CoreAnnotations.WordnetSynAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.WordnetSynAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.WordnetSynAnnotation
 
CoreAnnotations.WordPositionAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.WordPositionAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.WordPositionAnnotation
 
CoreAnnotations.WordSenseAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.WordSenseAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.WordSenseAnnotation
 
CoreAnnotations.XmlContextAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.XmlContextAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.XmlContextAnnotation
 
CoreAnnotations.XmlElementAnnotation - Class in edu.stanford.nlp.ling
Used in SimpleXMLAnnotator.
CoreAnnotations.XmlElementAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.XmlElementAnnotation
 
CoreAnnotations.YearAnnotation - Class in edu.stanford.nlp.ling
 
CoreAnnotations.YearAnnotation() - Constructor for class edu.stanford.nlp.ling.CoreAnnotations.YearAnnotation
 
coreKey - Variable in enum edu.stanford.nlp.ling.AnnotationLookup.KeyLookup
 
CoreLabel - Class in edu.stanford.nlp.ling
A CoreLabel is a Map from keys (which are Class objects) to values, whose type is determined by the key.
CoreLabel() - Constructor for class edu.stanford.nlp.ling.CoreLabel
Default constructor, calls super()
CoreLabel(int) - Constructor for class edu.stanford.nlp.ling.CoreLabel
Initializes this CoreLabel, pre-allocating arrays to hold up to capacity key,value pairs.
CoreLabel(CoreLabel) - Constructor for class edu.stanford.nlp.ling.CoreLabel
Returns a new CoreLabel instance based on the contents of the given CoreLabel.
CoreLabel(CoreMap) - Constructor for class edu.stanford.nlp.ling.CoreLabel
Returns a new CoreLabel instance based on the contents of the given CoreMap.
CoreLabel(Label) - Constructor for class edu.stanford.nlp.ling.CoreLabel
Returns a new CoreLabel instance based on the contents of the given label.
CoreLabel(String[], String[]) - Constructor for class edu.stanford.nlp.ling.CoreLabel
This constructor attempts to parse the String keys into Class keys.
CoreLabel.GenericAnnotation<T> - Interface in edu.stanford.nlp.ling
Class that all "generic" annotations extend.
CoreMap - Interface in edu.stanford.nlp.util
Base type for all annotatable core objects.
correct(double, int) - Static method in class edu.stanford.nlp.classify.PRCurve
 
cosine(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
countCloseToZero(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
Counter<E> - Interface in edu.stanford.nlp.stats
An Object to double map used for keeping weights or counts for objects.
counter - Variable in class edu.stanford.nlp.stats.Distribution
 
Counters - Class in edu.stanford.nlp.stats
Static methods for operating on Counters.
countInfinite(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
countNaN(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
countNegative(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
countNonZero(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
countPositive(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
covariance(double[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
cPosDef - Variable in class edu.stanford.nlp.optimization.SMDMinimizer
 
create() - Method in interface edu.stanford.nlp.util.Factory
Creates and returns a new instance of the given type.
create(String) - Static method in class edu.stanford.nlp.util.MetaClass
Creates a new MetaClass (helper method)
create(Class<?>) - Static method in class edu.stanford.nlp.util.MetaClass
Creates a new MetaClass (helper method)
createClassifier(double[]) - Method in interface edu.stanford.nlp.classify.ClassifierCreator
 
createClassifier(double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory.LinearClassifierCreator
 
createFactory(Class<?>...) - Method in class edu.stanford.nlp.util.MetaClass
Creates a factory for producing instances of this class from a constructor taking the given types as arguments
createFactory(String...) - Method in class edu.stanford.nlp.util.MetaClass
Creates a factory for producing instances of this class from a constructor taking the given types as arguments
createFactory(Object...) - Method in class edu.stanford.nlp.util.MetaClass
Creates a factory for producing instances of this class from a constructor taking objects of the types given
createIndex() - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
create an index for each parameter - the prior probs and the features with all of their values
createInstance(Object...) - Method in class edu.stanford.nlp.util.MetaClass.ClassFactory
Creates an instance of the class produced in this factory
createInstance(Object...) - Method in class edu.stanford.nlp.util.MetaClass
Create an instance of the class, inferring the type automatically, and given an array of objects as constructor parameters NOTE: the resulting instance will [unlike java] invoke the most narrow constructor rather than the one which matches the signature passed to this function
createInstance(Class<E>, Object...) - Method in class edu.stanford.nlp.util.MetaClass
Creates an instance of the class, forcing a cast to a certain type and given an array of objects as constructor parameters NOTE: the resulting instance will [unlike java] invoke the most narrow constructor rather than the one which matches the signature passed to this function
createLinearClassifier(double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory.LinearClassifierCreator
 
createProbabilisticClassifier(double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory.LinearClassifierCreator
 
createProbabilisticClassifier(double[]) - Method in interface edu.stanford.nlp.classify.ProbabilisticClassifierCreator
 
CRForder - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
crfType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
CRFwindow - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
cross(Set<E>, Set<F>) - Static method in class edu.stanford.nlp.util.Sets
Returns the set cross product of s1 and s2, as Pairs
CROSS_OUT - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
crossEntropy(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Note that this implementation doesn't normalize the "from" Counter.
crossValidateSetSigma(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Calls the method LinearClassifierFactory.crossValidateSetSigma(GeneralDataset, int) with 5-fold cross-validation.
crossValidateSetSigma(GeneralDataset<L, F>, int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
callls the method LinearClassifierFactory.crossValidateSetSigma(GeneralDataset, int, Scorer, LineSearcher) with multi-class log-likelihood scoring (see MultiClassAccuracyStats) and golden-section line search (see GoldenSectionLineSearch).
crossValidateSetSigma(GeneralDataset<L, F>, int, Scorer<L>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
crossValidateSetSigma(GeneralDataset<L, F>, int, LineSearcher) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
crossValidateSetSigma(GeneralDataset<L, F>, int, Scorer<L>, LineSearcher) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the sigma parameter to a value that optimizes the cross-validation score given by scorer.
CrossValidator<L,F> - Class in edu.stanford.nlp.classify
This class is meant to simplify performing cross validation on classifiers for hyper-parameters.
CrossValidator(GeneralDataset<L, F>) - Constructor for class edu.stanford.nlp.classify.CrossValidator
 
CrossValidator(GeneralDataset<L, F>, int) - Constructor for class edu.stanford.nlp.classify.CrossValidator
 
CrossValidator.SavedState - Class in edu.stanford.nlp.classify
 
CrossValidator.SavedState() - Constructor for class edu.stanford.nlp.classify.CrossValidator.SavedState
 
curElement - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
current() - Static method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
The current Redwood configuration; this is used to make incremental changes to an existing custom configuration.
cwa() - Method in class edu.stanford.nlp.classify.PRCurve
confidence weighted accuracy assuming the scores are probabilities and using .5 as treshold
cwaArray() - Method in class edu.stanford.nlp.classify.PRCurve
confidence weighted accuracy assuming the scores are probabilities and using .5 as treshold
CYAN - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 

D

d - Variable in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
d - Variable in class edu.stanford.nlp.optimization.ScaledSGDMinimizer.weight
 
data - Variable in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
data - Variable in class edu.stanford.nlp.classify.GeneralDataset
 
data - Variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
data - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
data - Variable in class edu.stanford.nlp.util.ArrayIterable
 
dataDimension() - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
dataDimension() - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
Data dimension must return the size of the data used by the function.
dataIterable - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
Dataset<L,F> - Class in edu.stanford.nlp.classify
An interfacing class for ClassifierFactory that incrementally builds a more memory-efficient representation of a List of Datum objects for the purposes of training a Classifier with a ClassifierFactory.
Dataset() - Constructor for class edu.stanford.nlp.classify.Dataset
 
Dataset(int, Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.Dataset
 
Dataset(Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.Dataset
 
Dataset(int) - Constructor for class edu.stanford.nlp.classify.Dataset
 
Dataset(Index<L>, int[], Index<F>, int[][]) - Constructor for class edu.stanford.nlp.classify.Dataset
Constructor that fully specifies a Dataset.
Dataset(Index<L>, int[], Index<F>, int[][], int) - Constructor for class edu.stanford.nlp.classify.Dataset
Constructor that fully specifies a Dataset.
dataweights - Variable in class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
dataweights - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
dataweights - Variable in class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
Datum<L,F> - Interface in edu.stanford.nlp.ling
Interface for Objects which can be described by their features.
DBG - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
DBG - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
debug(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
decreasePriority(E, double) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Demotes a key in the queue, adding it if it wasn't there already.
decrementBatch(int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
decrementBatch - This decrements the curElement variable by the amount batchSize.
decrementCount(E, double) - Method in class edu.stanford.nlp.stats.AbstractCounter
 
decrementCount(E) - Method in class edu.stanford.nlp.stats.AbstractCounter
 
decrementCount(E, double) - Method in class edu.stanford.nlp.stats.ClassicCounter
Decrements the count for this key by the given value.
decrementCount(E) - Method in class edu.stanford.nlp.stats.ClassicCounter
Decrements the count for this key by 1.0.
decrementCount(E, double) - Method in interface edu.stanford.nlp.stats.Counter
Decrements the count for this key by the given value.
decrementCount(E) - Method in interface edu.stanford.nlp.stats.Counter
Decrements the count for this key by 1.0.
decrementCount(E, int) - Method in class edu.stanford.nlp.stats.IntCounter
Subtracts the given count from the current count for the given key.
decrementCount(E) - Method in class edu.stanford.nlp.stats.IntCounter
Subtracts 1 from the count for the given key.
decrementCount(K1, K2) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
decrementCount(K1, K2, double) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
decrementCount(K1, K2) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
decrementCount(K1, K2, double) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
decrementCounts(Collection<E>, int) - Method in class edu.stanford.nlp.stats.IntCounter
Subtracts the given count from the current counts for each of the given keys.
decrementCounts(Collection<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Subtracts 1 from the counts of each of the given keys.
deepCopy(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
deepCopy(MapFactory<Object, BinaryHeapPriorityQueue.Entry<E>>) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
deepCopy() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
DEFAULT_BACKGROUND_SYMBOL - Static variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
defaultReturnValue() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns the default return value.
defaultReturnValue() - Method in interface edu.stanford.nlp.stats.Counter
Returns the default return value.
defaultReturnValue() - Method in class edu.stanford.nlp.stats.IntCounter
 
defaultReturnValue(double) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
defaultReturnValue() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
defaultReturnValue(double) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
defaultReturnValue() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
dehyphenateNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
delegate - Variable in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
deleteBlankLines - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
deleteOutofRange(Counter<E>, int, int) - Static method in class edu.stanford.nlp.stats.Counters
Delete 'top' and 'bottom' number of elements from the top and bottom respectively
deltaDecode(byte[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
deltaDecode(byte[], int, int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
deltaDecodeList(byte[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
deltaDecodeList(byte[], int, int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
deltaEncode(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
deltaEncodeList(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
depth - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
derivative - Variable in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
derivativeAD - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
derivativeAt(double[]) - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
derivativeAt(double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
derivativeAt(double[], double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
derivativeAt(float[]) - Method in interface edu.stanford.nlp.optimization.DiffFloatFunction
Returns the first-derivative vector at the input location.
derivativeAt(double[]) - Method in interface edu.stanford.nlp.optimization.DiffFunction
Returns the first-derivative vector at the input location.
derivativeNumerator - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
DESCENDING_COMPARATOR - Static variable in class edu.stanford.nlp.util.ScoredComparator
 
deserializeCounter(String) - Static method in class edu.stanford.nlp.stats.Counters
 
devFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
diag(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns diagonal elements of the given (square) matrix.
diag - Variable in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
dictionary - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
dictionary2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
diff(Counter<T>, Counter<T>) - Static method in class edu.stanford.nlp.stats.Counters
 
diff(Collection<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
all objects in list1 that are not in list2
diff(Set<E>, Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns the difference of sets s1 and s2.
DiffFloatFunction - Interface in edu.stanford.nlp.optimization
An interface for once-differentiable double-valued functions over double arrays.
DiffFunction - Interface in edu.stanford.nlp.optimization
An interface for once-differentiable double-valued functions over double arrays.
DIM - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
discretizeCompute(Function<Double, Double>, int, double, double) - Method in class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
disjunctionWidth - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
dispatchable(Object) - Static method in class edu.stanford.nlp.util.logging.PrettyLogger
Returns true if an object has special logic for pretty logging (e.g.
Distribution<E> - Class in edu.stanford.nlp.stats
Immutable class for representing normalized, smoothed discrete distributions from Counters.
distributionFromLogisticCounter(Counter<E>) - Static method in class edu.stanford.nlp.stats.Distribution
Maps a counter representing the linear weights of a multiclass logistic regression model to the probabilities of each class.
distributionWithDirichletPrior(Counter<E>, Distribution<E>, double) - Static method in class edu.stanford.nlp.stats.Distribution
Returns a Distribution that uses prior as a Dirichlet prior weighted by weight.
distSimFileFormat - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
The format of the distsim file.
distSimLexicon - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
distSimMaxBits - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
If this number is greater than 0, the distSim class is assume to be a bit string and is truncated at this many characters.
divide(DoubleAD, DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
divideConst(DoubleAD, double) - Static method in class edu.stanford.nlp.math.ADMath
 
divideInPlace(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Divides every non-zero count in target by the corresponding value in the denominator Counter.
divideInPlace(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Divides each value in target by the given divisor, in place.
division(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns c1 divided by c2.
doAdaptation - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
docID() - Method in class edu.stanford.nlp.ling.CoreLabel
docID() - Method in interface edu.stanford.nlp.ling.HasIndex
 
documentReader - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
doFE - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
doGibbs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
doing(String) - Method in class edu.stanford.nlp.util.Timing
Print the start of timing message to stderr and start the timer.
domain - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
domainDimension() - Method in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.BiasedLogisticObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction
 
domainDimension() - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
domainDimension() - Method in interface edu.stanford.nlp.optimization.FloatFunction
Returns the number of dimensions in the function's domain
domainDimension() - Method in interface edu.stanford.nlp.optimization.Function
Returns the number of dimensions in the function's domain
done() - Method in class edu.stanford.nlp.util.Timing
Finish the line from startDoing with the end of the timing done message and elapsed time in x.y seconds.
done(String) - Method in class edu.stanford.nlp.util.Timing
Give a line saying that something is " done".
dontExtendTaggy - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
dontPrintChannels() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
Do not print a margin with the channels corresponding to a log entry.
dotProduct(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the product of c1 and c2.
dotProduct(Counter<E>, double[], Index<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the product of Counter c and double[] a, using Index idx to map entries in C onto a.
dotProductInPlace(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Multiplies every count in target by the corresponding value in the term Counter.
DoubleAD - Class in edu.stanford.nlp.math
The class DoubleAD was created to extend the current calculations of gradient to automatically include a calculation of the hessian vector product with another vector v.
DoubleAD() - Constructor for class edu.stanford.nlp.math.DoubleAD
 
DoubleAD(double, double) - Constructor for class edu.stanford.nlp.math.DoubleAD
 
doubleArrayToFloatArray(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
doubleArrayToFloatArray(double[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
doubleMax() - Method in class edu.stanford.nlp.stats.IntCounter
 
doubleValue() - Method in class edu.stanford.nlp.math.DoubleAD
 
doubleValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
doubleValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
drawSample() - Method in class edu.stanford.nlp.stats.Distribution
Exactly the same as sampleFrom(), needed for the Sampler interface.
drawSample(Random) - Method in class edu.stanford.nlp.stats.Distribution
A method to draw a sample, providing an own random number generator.
drawSample(Random) - Method in interface edu.stanford.nlp.stats.ProbabilityDistribution
 
drawSample() - Method in interface edu.stanford.nlp.stats.Sampler
 
dropGaz - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
dump() - Method in class edu.stanford.nlp.classify.LinearClassifier
Print all features in the classifier and the weight that they assign to each class.
dump(PrintWriter) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
dump - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
dumpMemory() - Method in class edu.stanford.nlp.optimization.GoldenSectionLineSearch
dump the pairs it computed found
dumpSorted() - Method in class edu.stanford.nlp.classify.LinearClassifier
Print all features in the classifier and the weight that they assign to each class.
dynamicCounterWithDirichletPrior(Counter<E>, Distribution<E>, double) - Static method in class edu.stanford.nlp.stats.Distribution
Like normalizedCounterWithDirichletPrior except probabilities are computed dynamically from the counter and prior instead of all at once up front.

E

editDistance(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Computes the Levenshtein (edit) distance of the two given Strings.
edu.stanford.nlp.classify - package edu.stanford.nlp.classify
The classify package provides facilities for training classifiers.
edu.stanford.nlp.io - package edu.stanford.nlp.io
 
edu.stanford.nlp.ling - package edu.stanford.nlp.ling
 
edu.stanford.nlp.math - package edu.stanford.nlp.math
 
edu.stanford.nlp.objectbank - package edu.stanford.nlp.objectbank
 
edu.stanford.nlp.optimization - package edu.stanford.nlp.optimization
 
edu.stanford.nlp.process - package edu.stanford.nlp.process
 
edu.stanford.nlp.sequences - package edu.stanford.nlp.sequences
 
edu.stanford.nlp.stats - package edu.stanford.nlp.stats
 
edu.stanford.nlp.util - package edu.stanford.nlp.util
 
edu.stanford.nlp.util.concurrent - package edu.stanford.nlp.util.concurrent
 
edu.stanford.nlp.util.logging - package edu.stanford.nlp.util.logging
 
elems() - Method in class edu.stanford.nlp.util.IntTuple
 
EMPTY - Static variable in class edu.stanford.nlp.ling.Word
Word representation of an empty.
EMPTY - Static variable in class edu.stanford.nlp.util.logging.LogRecordHandler
An empty list to serve as the FALSE token for filters
empty() - Static method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
An empty Redwood configuration.
EMPTY_STRING_ARRAY - Static variable in class edu.stanford.nlp.util.StringUtils
 
EMPTYSTRING - Static variable in class edu.stanford.nlp.ling.Word
String representation of an empty.
enc - Variable in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
The encoding for file input.
encodedInputStreamReader(InputStream, String) - Static method in class edu.stanford.nlp.io.IOUtils
Create a Reader with an explicit encoding around an InputStream.
encodedOutputStreamPrintWriter(OutputStream, String, boolean) - Static method in class edu.stanford.nlp.io.IOUtils
Create a Reader with an explicit encoding around an InputStream.
encodedOutputStreamWriter(OutputStream, String) - Static method in class edu.stanford.nlp.io.IOUtils
Create a Reader with an explicit encoding around an InputStream.
EncodingFileReader - Class in edu.stanford.nlp.io
This is a convenience class which works almost exactly like FileReader but allows for the specification of input encoding.
EncodingFileReader(String) - Constructor for class edu.stanford.nlp.io.EncodingFileReader
Creates a new EncodingFileReader, given the name of the file to read from.
EncodingFileReader(String, String) - Constructor for class edu.stanford.nlp.io.EncodingFileReader
Creates a new EncodingFileReader, given the name of the file to read from and an encoding
EncodingFileReader(File) - Constructor for class edu.stanford.nlp.io.EncodingFileReader
Creates a new EncodingFileReader, given the File to read from, and using default of utf-8.
EncodingFileReader(File, String) - Constructor for class edu.stanford.nlp.io.EncodingFileReader
Creates a new FileReader, given the File to read from and encoding.
EncodingFileReader(FileDescriptor) - Constructor for class edu.stanford.nlp.io.EncodingFileReader
Creates a new FileReader, given the FileDescriptor to read from.
end_Track(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
end_track() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
endDoing() - Static method in class edu.stanford.nlp.util.Timing
Finish the line from startDoing with the end of the timing done message and elapsed time in x.y seconds.
endDoing(String) - Static method in class edu.stanford.nlp.util.Timing
Finish the line from startDoing with the end of the timing done message and elapsed time in x.y seconds.
endFold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
endPosition() - Method in class edu.stanford.nlp.ling.CoreLabel
 
endPosition() - Method in interface edu.stanford.nlp.ling.HasOffset
Return the ending character offset of the label (or -1 if none).
endPosition() - Method in class edu.stanford.nlp.ling.StringLabel
 
endThreads(String) - Static method in class edu.stanford.nlp.util.logging.Redwood
Signal that all threads have run to completion, and the multithreaded environment is over.
endThreads(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
endTime() - Static method in class edu.stanford.nlp.util.Timing
Return elapsed time on (static) timer (without stopping timer).
endTime(String, PrintStream) - Static method in class edu.stanford.nlp.util.Timing
Print elapsed time on (static) timer (without stopping timer).
endTime(String) - Static method in class edu.stanford.nlp.util.Timing
Print elapsed time on (static) timer to System.err (without stopping timer).
endTrack(String) - Static method in class edu.stanford.nlp.util.logging.Redwood
End a "track;" that is, return to logging at one level shallower.
endTrack() - Static method in class edu.stanford.nlp.util.logging.Redwood
A utility method for closing calls to the anonymous startTrack() call.
endTrack(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
endTrack() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
ensureDir(File) - Static method in class edu.stanford.nlp.io.IOUtils
Given a filepath, makes sure a directory exists there.
ensureRealValues() - Method in class edu.stanford.nlp.classify.RVFDataset
Checks if the dataset has any unbounded values.
ensureSize() - Method in class edu.stanford.nlp.classify.Dataset
 
ensureSize() - Method in class edu.stanford.nlp.classify.WeightedDataset
 
entitySubclassification - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
entropy(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Calculates the entropy of the given counter (in bits).
entrySet() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns a view of the entries in this counter.
entrySet() - Method in interface edu.stanford.nlp.stats.Counter
Returns a view of the entries in this counter.
entrySet() - Method in class edu.stanford.nlp.stats.IntCounter
Returns a view of the doubles in this map.
entrySet() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
entrySet() - Method in class edu.stanford.nlp.util.ArrayMap
 
eolChar - Static variable in class edu.stanford.nlp.io.IOUtils
 
epsilon - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
equalContents(int[][], int[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Tests two int[][] arrays for having equal contents.
equalContents(int[], int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
tests two int[] arrays for having equal contents
equals(Object) - Method in class edu.stanford.nlp.ling.BasicDatum
Returns whether the given Datum contains the same features as this Datum.
equals(Object) - Method in class edu.stanford.nlp.ling.RVFDatum
Returns whether the given RVFDatum contains the same features with the same values as this RVFDatum.
equals(Object) - Method in class edu.stanford.nlp.ling.ValueLabel
Equality for ValueLabels is defined in the first instance as equality of their String value().
equals(Object) - Method in class edu.stanford.nlp.ling.WordLemmaTag
Equality is satisfied only if the compared object is a WordLemmaTag and has String-equal word, lemma and tag fields.
equals(Object) - Method in class edu.stanford.nlp.ling.WordTag
A WordTag is equal only to another WordTag with the same word and tag values.
equals(DoubleAD) - Method in class edu.stanford.nlp.math.DoubleAD
 
equals(double, double) - Method in class edu.stanford.nlp.math.DoubleAD
 
equals(double, double, double) - Method in class edu.stanford.nlp.math.DoubleAD
 
equals(Object) - Method in class edu.stanford.nlp.stats.ClassicCounter
Equality is defined over all Counter implementations.
equals(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Default equality comparison for two counters potentially backed by alternative implementations.
equals(Object) - Method in class edu.stanford.nlp.stats.Distribution
 
equals(Distribution<E>) - Method in class edu.stanford.nlp.stats.Distribution
 
equals(Object) - Method in class edu.stanford.nlp.stats.IntCounter
 
equals(Object) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
equals(Object) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Two CoreMaps are equal iff all keys and values are .equal.
equals(Object) - Method in class edu.stanford.nlp.util.ArrayMap
 
equals(double[][], double[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Tests two double[][] arrays for having equal contents.
equals(boolean[][], boolean[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Tests two boolean[][] arrays for having equal contents.
equals(Object) - Method in class edu.stanford.nlp.util.HashableCoreMap
If the provided object is a HashableCoreMap, equality is based only upon the values of the immutable hashkeys; otherwise, defaults to behavior of the superclass's equals method.
equals(Object) - Method in class edu.stanford.nlp.util.Interval
 
equals(Object) - Method in class edu.stanford.nlp.util.IntPair
 
equals(Object) - Method in class edu.stanford.nlp.util.IntTuple
 
equals(Redwood.Record, Redwood.Record) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ApproximateRepeatSemantics
 
equals(Redwood.Record, Redwood.Record) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ExactRepeatSemantics
 
equals(Redwood.Record, Redwood.Record) - Method in interface edu.stanford.nlp.util.logging.RepeatedRecordHandler.RepeatSemantics
 
equals(Object) - Method in class edu.stanford.nlp.util.MetaClass.ClassFactory
 
equals(Object) - Method in class edu.stanford.nlp.util.MetaClass
 
equals(Object) - Method in class edu.stanford.nlp.util.MutableDouble
Compares this object to the specified object.
equals(Object) - Method in class edu.stanford.nlp.util.MutableInteger
Compares this object to the specified object.
equals(Object) - Method in class edu.stanford.nlp.util.Pair
 
equals(Object) - Method in class edu.stanford.nlp.util.ScoredComparator
 
equals(Object) - Method in class edu.stanford.nlp.util.Triple
 
ErasureUtils - Class in edu.stanford.nlp.util
Class to gather unsafe operations into one place.
err() - Static method in class edu.stanford.nlp.util.logging.Redwood.ConsoleHandler
 
ERR - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
ERR - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
err(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
escapeString(String, char[], char) - Static method in class edu.stanford.nlp.util.StringUtils
 
estimateInitial - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
evalCmd - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
evaluate(double[]) - Method in interface edu.stanford.nlp.optimization.Evaluator
 
evaluateIOB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
evaluateIters - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
evaluateTrain - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
Evaluator - Interface in edu.stanford.nlp.optimization
 
EXACT - Static variable in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
 
exactBinomial(int, int, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Find a one tailed exact binomial test probability.
exit(int) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
exit() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
exp(DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
exp(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
exp(Counter<T>) - Static method in class edu.stanford.nlp.stats.Counters
 
expand(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Returns (smallest) interval that contains both this and the other interval
expandMidDot - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
experimentalClassOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
expInPlace(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
expInPlace(Counter<T>) - Static method in class edu.stanford.nlp.stats.Counters
 
exportFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
extractRelationSubflags(int, int) - Static method in class edu.stanford.nlp.util.Interval
 

F

f1(int, int, int) - Static method in class edu.stanford.nlp.classify.PRCurve
 
factorial(int) - Static method in class edu.stanford.nlp.math.SloppyMath
Uses floating point so that it can represent the really big numbers that come up.
factory() - Static method in class edu.stanford.nlp.ling.CoreLabel
Return a factory for this kind of label
factory() - Static method in class edu.stanford.nlp.ling.StringLabel
Return a factory for this kind of label.
factory() - Static method in class edu.stanford.nlp.ling.TaggedWord
Return a factory for this kind of label.
factory() - Static method in class edu.stanford.nlp.ling.Word
Return a factory for this kind of label.
factory() - Static method in class edu.stanford.nlp.ling.WordTag
Return a factory for this kind of label.
Factory<T> - Interface in edu.stanford.nlp.util
A generified factory class which creates instances of a particular type.
fail(Object) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
fail() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
fakeDataset - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featThreshFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featureCountThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featureDiffThresh - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featureFactory - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featureIndex - Variable in class edu.stanford.nlp.classify.GeneralDataset
 
featureIndex() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
featureIndex() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
featureIndex - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
features() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
featureThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
featureWeightThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
Featurizable<F> - Interface in edu.stanford.nlp.ling
Interface for Objects that can be described by their features.
femaleNameList - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
file - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
file(String) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a file pipeline to the Redwood handler tree.
fileNameClean(String) - Static method in class edu.stanford.nlp.util.StringUtils
Returns a "clean" version of the given filename in which spaces have been converted to dashes and all non-alphanumeric chars are underscores.
fill(double[][], double) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
fill(double[][][], double) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
fill(double[][][][], double) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
fill(boolean[][], boolean) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
fill(boolean[][][], boolean) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
fill(boolean[][][][], boolean) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
Filter<T> - Interface in edu.stanford.nlp.util
Filter is an interface for predicate objects which respond to the accept method.
filterInfinite(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
filterNaN(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
filterNaNAndInfinite(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
filterStackTrace(StackTraceElement[]) - Static method in class edu.stanford.nlp.util.logging.Redwood
Removes logging classes from a stack trace.
find(LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
find(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Say whether this regular expression can be found inside this String.
finishThread() - Static method in class edu.stanford.nlp.util.logging.Redwood
Signal that this thread will not log any more messages in the multithreaded environment
finishThread() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
finiteDifferenceStepSize - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
finiteDifferenceStepSize - this is the fixed step size for the finite difference approximation.
first - Variable in class edu.stanford.nlp.util.Pair
Direct access is deprecated.
first() - Method in class edu.stanford.nlp.util.Pair
 
first - Variable in class edu.stanford.nlp.util.Triple
 
first() - Method in class edu.stanford.nlp.util.Triple
 
firstKeySet() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
firstKeySet() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
FixedPrioritiesPriorityQueue<E> - Class in edu.stanford.nlp.util
A priority queue based on a binary heap.
FixedPrioritiesPriorityQueue() - Constructor for class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
FixedPrioritiesPriorityQueue(int) - Constructor for class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
flatten() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
flatten(double[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
flatten(Collection<List<T>>) - Static method in class edu.stanford.nlp.util.CollectionUtils
combines all the lists in a collection to a single list
floatArrayToDoubleArray(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
floatArrayToDoubleArray(float[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
FloatFunction - Interface in edu.stanford.nlp.optimization
An interface for double-valued functions over double arrays.
floatValue() - Method in class edu.stanford.nlp.math.DoubleAD
 
floatValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
floatValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
flush() - Method in class edu.stanford.nlp.io.BZip2PipedOutputStream
 
flush() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
fmeasure(int, int) - Method in class edu.stanford.nlp.classify.PRCurve
the f-measure if we just guess as negativ the first numleft and guess as poitive the last numright
fmeasure(int) - Method in class edu.stanford.nlp.classify.PRCurve
what is the f-measure at this recall if we look at the score as the probability of class 1 given x as if coming from logistic regression same as logPrecision but calculating f-measure
FORCE - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
force() - Method in class edu.stanford.nlp.util.logging.Redwood.Record
Returns whether this log message wants to be forced to be printed
FORCE - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
force_track(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
forceTrack(Object) - Static method in class edu.stanford.nlp.util.logging.Redwood
Helper method to start a track on the FORCE channel.
forceTrack() - Static method in class edu.stanford.nlp.util.logging.Redwood
Helper method to start an anonymous track on the FORCE channel.
forceTrack(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
format(String, Object...) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
format(Locale, String, Object...) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
formatTimeDifference(long, StringBuilder) - Static method in class edu.stanford.nlp.util.logging.Redwood
Utility method for formatting a time difference (maybe this should go to a util class?)
free() - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
fromMap(Map<E, N>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a counter view of the given map.
fromMap(Map<E, N>, Class<N>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a counter view of the given map.
fromString(String) - Static method in class edu.stanford.nlp.stats.ClassicCounter
Converts from the format printed by the toString method back into a Counter<String>.
Function - Interface in edu.stanford.nlp.optimization
An interface for double-valued functions over double arrays.
Function<T1,T2> - Interface in edu.stanford.nlp.util
An interface for classes that act as a function transforming one object to another.

G

gain - Variable in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
gain - Static variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
gainSchedule(int, double) - Static method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
gainSGD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
gamma(double) - Static method in class edu.stanford.nlp.math.SloppyMath
 
gapDecode(byte[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gapDecode(byte[], int, int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gapDecodeList(byte[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gapDecodeList(byte[], int, int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gapEncode(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gapEncodeList(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
gazettes - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
gazFilesFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
gen - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
gen - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
GeneralDataset<L,F> - Class in edu.stanford.nlp.classify
The purpose of this interface is to unify Dataset and RVFDataset.
GeneralDataset() - Constructor for class edu.stanford.nlp.classify.GeneralDataset
 
GeneralizedExpectationObjectiveFunction<L,F> - Class in edu.stanford.nlp.classify
Implementation of Generalized Expectation Objective function for an I.I.D.
GeneralizedExpectationObjectiveFunction(GeneralDataset<L, F>, List<? extends Datum<L, F>>, List<F>) - Constructor for class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
genericKeys - Static variable in class edu.stanford.nlp.ling.CoreLabel
 
Generics - Class in edu.stanford.nlp.util
A collection of utilities to make dealing with Java generics less painful and verbose.
genericValues - Static variable in class edu.stanford.nlp.ling.CoreLabel
 
get(Class<KEY>) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Returns the value associated with the given key or null if none is provided.
get(Object) - Method in class edu.stanford.nlp.util.ArrayMap
 
get(int) - Method in class edu.stanford.nlp.util.HashIndex
Gets the object whose index is the integer argument.
get(int) - Method in interface edu.stanford.nlp.util.Index
Gets the object whose index is the integer argument.
get(int) - Method in class edu.stanford.nlp.util.IntTuple
 
get(Class<KEY>) - Method in interface edu.stanford.nlp.util.TypesafeMap
Returns the value associated with the given key or null if none is provided.
getAccCoverage() - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
getAdaptationPrior(double[], LogPrior) - Static method in class edu.stanford.nlp.classify.LogPrior
 
getBaseName(String) - Static method in class edu.stanford.nlp.util.StringUtils
Strip directory from filename.
getBaseName(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Strip directory and suffix from filename.
getBatch(int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
getBatch is used to generate the next sequence of indices to be passed to the actual function.
getBegin() - Method in class edu.stanford.nlp.util.Interval
Returns the start point
getBufferedFileReader(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getBufferedFileReader(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getBZip2PipedInputStream(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getBZip2PipedOutputStream(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getClassifierCreator(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
getCopy(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
getCopy() - Method in class edu.stanford.nlp.util.IntPair
 
getCopy() - Method in class edu.stanford.nlp.util.IntQuadruple
 
getCopy() - Method in class edu.stanford.nlp.util.IntTriple
 
getCopy() - Method in class edu.stanford.nlp.util.IntTuple
 
getCopy() - Method in class edu.stanford.nlp.util.IntUni
 
getCoreKey(String) - Static method in class edu.stanford.nlp.ling.AnnotationLookup
Returns a CoreAnnotation class key for the given old-style FeatureLabel key if one exists; null otherwise.
getCount(Object) - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns the count for this key as a double.
getCount(Object) - Method in interface edu.stanford.nlp.stats.Counter
Returns the count for this key as a double.
getCount(E) - Method in class edu.stanford.nlp.stats.Distribution
Returns the current count for the given key, which is 0 if it hasn't been seen before.
getCount(Object) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the current count for the given key, which is 0 if it hasn't been seen before.
getCount(K1, K2) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
getCount(K1, K2) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
getCountAsString(E) - Method in class edu.stanford.nlp.stats.IntCounter
 
getCountCounts(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
getCounter() - Method in class edu.stanford.nlp.stats.Distribution
 
getCounter(K1) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
getCounter(K1) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
getDataArray() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
getDatum(int) - Method in class edu.stanford.nlp.classify.Dataset
 
getDatum(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
getDatum(int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
getDescription(int) - Method in class edu.stanford.nlp.stats.AccuracyStats
 
getDescription(int) - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
getDescription(int) - Method in interface edu.stanford.nlp.stats.Scorer
 
getDiag(String) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
getDistribution(Counter<E>) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a Distribution from the given counter.
getDistributionFromLogValues(Counter<E>) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a Distribution from the given counter, ie makes an internal copy of the counter and divides all counts by the total count.
getDistributionFromPartiallySpecifiedCounter(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Distribution
Assuming that c has a total count < 1, returns a new Distribution using the counts in c as probabilities.
getDistributionWithReservedMass(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Distribution
 
getdot() - Method in class edu.stanford.nlp.math.DoubleAD
 
getEnd() - Method in class edu.stanford.nlp.util.Interval
Returns the end point
getEpsilon() - Method in class edu.stanford.nlp.classify.LogPrior
 
getExtension(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getFactory() - Static method in class edu.stanford.nlp.objectbank.LineIterator
Returns a factory that vends LineIterators that read the contents of the given Reader, splitting on newlines.
getFactory(Function<String, X>) - Static method in class edu.stanford.nlp.objectbank.LineIterator
Returns a factory that vends LineIterators that read the contents of the given Reader, splitting on newlines.
getFactory() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns a factory that can create new instances of this kind of Counter.
getFactory() - Method in interface edu.stanford.nlp.stats.Counter
Returns a factory that can create new instances of this kind of Counter.
getFactory() - Method in class edu.stanford.nlp.stats.IntCounter
 
getFeatureCount(double, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns number of features with weight above a certain threshold (across all labels)
getFeatureCount(Set<L>, double, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns number of features with weight above a certain threshold
getFeatureCount(F) - Method in class edu.stanford.nlp.ling.RVFDatum
 
getFeatureCounter() - Method in class edu.stanford.nlp.classify.Dataset
Get Number of datums a given feature appears in.
getFeatureCountLabelIndices(Set<Integer>, double, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns number of features with weight above a certain threshold
getFeatureCounts() - Method in class edu.stanford.nlp.classify.GeneralDataset
Get the total count (over all data instances) of each feature
getFeatureCounts() - Method in class edu.stanford.nlp.classify.WeightedDataset
 
getFeatureIndex() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
getFileInputStream(String) - Static method in class edu.stanford.nlp.io.IOUtils
Get a input file stream (automatically gunzip/bunzip2 depending on file extension)
getFileOutputStream(String) - Static method in class edu.stanford.nlp.io.IOUtils
Get a output file stream (automatically gzip/bzip2 depending on file extension)
getFirst() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Finds the object with the highest priority and returns it, without modifying the queue.
getFirst() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns the highest-priority element without removing it from the queue.
getFirst() - Method in interface edu.stanford.nlp.util.PriorityQueue
Finds the object with the highest priority and returns it, without modifying the queue.
getGlobal() - Static method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
For getting the instance that global methods use.
getGlobal() - Static method in class edu.stanford.nlp.util.Interner
For getting the instance that global methods use.
getIndex(List<T>, T) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns the index of the first occurrence in the list of the specified object, using object identity (==) not equality as the criterion for object presence.
getIndex(List<T>, T, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns the index of the first occurrence after the startIndex (exclusive) in the list of the specified object, using object equals function.
getInformationGains() - Method in class edu.stanford.nlp.classify.Dataset
 
getInnerMapFactory() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
getInputStream() - Method in class edu.stanford.nlp.util.ByteStreamGobbler
 
getInputStreamFromURLOrClasspathOrFileSystem(String) - Static method in class edu.stanford.nlp.io.IOUtils
Locates this file either using the given URL, or in the CLASSPATH, or in the file system The CLASSPATH takes priority over the file system! This stream is buffered and gzipped (if necessary)
getIntCount(Object) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the current count for the given key, which is 0 if it hasn't been seen before.
getInterval() - Method in interface edu.stanford.nlp.util.HasInterval
 
getInterval() - Method in class edu.stanford.nlp.util.Interval
Returns this interval
getIntTuple(int) - Static method in class edu.stanford.nlp.util.IntTuple
 
getIntTuple(List<Integer>) - Static method in class edu.stanford.nlp.util.IntTuple
 
getIterator(Reader) - Method in interface edu.stanford.nlp.objectbank.IteratorFromReaderFactory
Return an iterator over the contents read from r.
getIterator(Reader) - Method in class edu.stanford.nlp.objectbank.LineIterator.LineIteratorFactory
 
getJNLPLocalScratch() - Static method in class edu.stanford.nlp.io.IOUtils
A JavaNLP specific convenience routine for obtaining the current scratch directory for the machine you're currently running on.
getL1NormalizedTFIDFDataset() - Method in class edu.stanford.nlp.classify.Dataset
Method to convert this dataset to RVFDataset using L1-normalized TF-IDF features
getL1NormalizedTFIDFDatum(Datum<L, F>, Counter<F>) - Method in class edu.stanford.nlp.classify.Dataset
Method to convert features from counts to L1-normalized TFIDF based features
getLabelForInternalNegativeClass() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
getLabelForInternalPositiveClass() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
getLabelIndices(Set<L>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns indices of labels
getLabelsArray() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
getLineIterator(String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(String, Function<String, X>) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(String, String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(Reader) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(Reader, Function<String, X>) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(File) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(File, Function<String, X>) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(File, String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(File, Function<String, X>, String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(Collection<?>, Function<String, X>) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(Collection<?>, String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getLineIterator(Collection<?>, Function<String, X>, String) - Static method in class edu.stanford.nlp.objectbank.ObjectBank
 
getListComparator() - Static method in class edu.stanford.nlp.util.CollectionUtils
 
getMapFactory() - Method in class edu.stanford.nlp.stats.IntCounter
 
getMapFromString(String, Class<K>, Class<V>, MapFactory<K, V>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
getMiddle() - Method in class edu.stanford.nlp.util.IntQuadruple
 
getMiddle() - Method in class edu.stanford.nlp.util.IntTriple
 
getName() - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.SQNMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
getName() - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
getName() - Method in class edu.stanford.nlp.util.MetaClass.ClassFactory
Returns the full class name for the objects being produced
getNGrams(List<T>, int, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Get all sub-lists of the given list of the given sizes.
getNormalizedCount(E) - Method in class edu.stanford.nlp.stats.IntCounter
This has been de-deprecated in order to reduce compilation warnings, but really you should create a Distribution instead of using this method.
getNotNullString(String) - Static method in class edu.stanford.nlp.util.StringUtils
 
getNotNullTrueStringRep() - Method in class edu.stanford.nlp.sequences.SeqClassifierFlags
note that this does *not* return string representation of arrays, lists and enums
getNumberOfKeys() - Method in class edu.stanford.nlp.stats.Distribution
 
getObject(E) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Searches for the object in the queue and returns it.
getObjective(AbstractStochasticCachingDiffUpdateFunction, double[], double, int[]) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
getOuterMapFactory() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
getOutputStream() - Method in class edu.stanford.nlp.util.ByteStreamGobbler
 
getPerturbedDistribution(Counter<E>, Random) - Static method in class edu.stanford.nlp.stats.Distribution
 
getPerturbedUniformDistribution(Set<E>, Random) - Static method in class edu.stanford.nlp.stats.Distribution
 
getPrefixesAndSuffixes(List<T>, int, int, T, boolean, boolean) - Static method in class edu.stanford.nlp.util.CollectionUtils
Get all prefix/suffix combinations from a list.
getPrintWriter(File) - Static method in class edu.stanford.nlp.io.IOUtils
 
getPrintWriter(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getPrintWriter(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
 
getPriority() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Gets the priority of the highest-priority element of the queue.
getPriority(E) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Get the priority of a key -- if the key is not in the queue, Double.NEGATIVE_INFINITY is returned.
getPriority(Object) - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Note that this method will be linear (not constant) time in this implementation! Better not to use it.
getPriority() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Gets the priority of the highest-priority element of the queue.
getPriority() - Method in interface edu.stanford.nlp.util.PriorityQueue
Gets the priority of the highest-priority element of the queue (without modifying the queue).
getPriority(E) - Method in interface edu.stanford.nlp.util.PriorityQueue
Get the priority of a key.
getProbabilities() - Method in class edu.stanford.nlp.stats.SimpleGoodTuring
Returns the probabilities allocated to each type, according to their count in the underlying collection.
getProbabilityForUnseen() - Method in class edu.stanford.nlp.stats.SimpleGoodTuring
Returns the probability allocated to types not seen in the underlying collection.
getRandomSubDataset(double, int) - Method in class edu.stanford.nlp.classify.Dataset
 
getRelation(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Returns the relationship of this interval to the other interval The most specific relationship from the following is returned.
getRelationFlags(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Return set of flags indicating possible relationships between this interval and another interval.
getReservedMass() - Method in class edu.stanford.nlp.stats.Distribution
 
getRho(int) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
getRVFDatum(int) - Method in class edu.stanford.nlp.classify.Dataset
 
getRVFDatum(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
getRVFDatum(int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
getRVFDatumId(int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
getRVFDatumSource(int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
getS(int) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
getSample(int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffUpdateFunction
Gets a random sample (this is sampling with replacement)
getShortClassName(Object) - Static method in class edu.stanford.nlp.util.StringUtils
Returns a short class name for an object.
getSigma() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
getSigma() - Method in class edu.stanford.nlp.classify.LogPrior
 
getSigmaSquared() - Method in class edu.stanford.nlp.classify.LogPrior
 
getSigmaSquaredM() - Method in class edu.stanford.nlp.classify.LogPrior
 
getSource() - Method in class edu.stanford.nlp.util.IntPair
 
getSource() - Method in class edu.stanford.nlp.util.IntQuadruple
 
getSource() - Method in class edu.stanford.nlp.util.IntTriple
 
getSource() - Method in class edu.stanford.nlp.util.IntUni
 
getString(Class<KEY>) - Method in class edu.stanford.nlp.ling.CoreLabel
Return a non-null String value for a key.
getTarget() - Method in class edu.stanford.nlp.util.IntPair
 
getTarget() - Method in class edu.stanford.nlp.util.IntQuadruple
 
getTarget() - Method in class edu.stanford.nlp.util.IntTriple
 
getTarget2() - Method in class edu.stanford.nlp.util.IntQuadruple
 
getTopFeatures(double, boolean, int) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns list of top features with weight above a certain threshold (list is descending and across all labels)
getTopFeatures(Set<L>, double, boolean, int, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns list of top features with weight above a certain threshold
getTopFeaturesLabelIndices(Set<Integer>, double, boolean, int, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns list of top features with weight above a certain threshold
getType(String) - Static method in class edu.stanford.nlp.classify.LogPrior
 
getType() - Method in class edu.stanford.nlp.classify.LogPrior
 
getType() - Method in interface edu.stanford.nlp.ling.CoreAnnotation
Returns the type associated with this annotation.
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AbbrAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AbgeneAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AbstrAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AfterAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AnswerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AnswerObjectAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.AntecedentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ArgDescendentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ArgumentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BagOfWordsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BeforeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BeginIndexAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BestCliquesAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.BestFullAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CalendarAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CategoryAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CategoryFunctionalTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CharacterOffsetBeginAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CharacterOffsetEndAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CharAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ChineseCharAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ChineseIsSegmentedAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ChineseOrigSegAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ChineseSegAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ChunkAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoarseTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CommonWordsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepParentIndexAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoNLLDepTypeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoNLLPredicateAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CoNLLSRLAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ContextsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CopyAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CostMagnificationAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.CovertIDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.D2_LBeginAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.D2_LEndAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.D2_LMiddleAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DayAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DependentsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DictAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DistSimAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DoAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DocDateAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DocIDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.DomainAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.EndIndexAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.EntityClassAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.EntityRuleAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.EntityTypeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.FeaturesAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.FemaleGazAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.FirstChildAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ForcedSentenceEndAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.FreqAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GazAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GazetteerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GenericTokensAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GeniaAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GoldAnswerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GovernorAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.GrandparentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.HaveAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.HeadWordStringAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.HeightAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.IDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.IDFAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.INAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.IndexAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.InterpretationAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.IsDateRangeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.IsURLAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LabelAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LabelWeightAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LastGazAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LastTaggedAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LBeginAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LeftChildrenNodeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LeftTermAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LemmaAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LEndAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LengthAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.LMiddleAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MaleGazAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MarkingAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MonthAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MorphoCaseAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MorphoGenAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MorphoNumAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.MorphoPersAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NamedEntityTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NeighborsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NERIDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NormalizedNamedEntityTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NotAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeObjectAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeTypeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericCompositeValueAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericObjectAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericTypeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumericValueAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumerizedTokensAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.NumTxtSentencesAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.OriginalAnswerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.OriginalCharAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.OriginalTextAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ParagraphAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ParagraphsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ParaPositionAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ParentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PartOfSpeechAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PercentAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PhraseWordsAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PhraseWordsTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PolarityAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PositionAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PossibleAnswersAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PredictedAnswerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PrevChildAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.PriorAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ProjectedCategoryAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ProtoAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.RoleAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SectionAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SemanticHeadTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SemanticHeadWordAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SemanticTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SemanticWordAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SentenceIDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SentenceIndexAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SentencePositionAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SentencesAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ShapeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SpaceBeforeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SpanAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SpeakerAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SRLIDAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SRLInstancesAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.StackedNamedEntityTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.StateAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.StemAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.SubcategorizationAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TagLabelAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TextAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TokenBeginAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TokenEndAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TokensAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TopicAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TrueCaseAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TrueCaseTextAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.TrueTagAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.UBlockAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.UnaryAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.UnknownAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.UtteranceAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.UTypeAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.ValueAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.VerbSenseAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.WebAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.WordFormAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.WordnetSynAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.WordPositionAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.WordSenseAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.XmlContextAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.XmlElementAnnotation
 
getType() - Method in class edu.stanford.nlp.ling.CoreAnnotations.YearAnnotation
 
getUniformDistribution(Set<E>) - Static method in class edu.stanford.nlp.stats.Distribution
 
getval() - Method in class edu.stanford.nlp.math.DoubleAD
 
getValuesArray() - Method in class edu.stanford.nlp.classify.Dataset
 
getValuesArray() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
getValuesArray() - Method in class edu.stanford.nlp.classify.RVFDataset
 
getValueType(Class<? extends CoreAnnotation>) - Static method in class edu.stanford.nlp.ling.AnnotationLookup
Returns the runtime value type associated with the given key.
getVariance(double[]) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
getVariance(double[], int) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
getWeights() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
getWeights() - Method in class edu.stanford.nlp.classify.WeightedDataset
 
getWeights(String) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
getY(int) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
globalIntern(T) - Static method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
Returns a unique object o' that .equals the argument o.
globalIntern(T) - Static method in class edu.stanford.nlp.util.Interner
Returns a unique object o' that .equals the argument o.
globalMutex - Static variable in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
GoldenSectionLineSearch - Class in edu.stanford.nlp.optimization
A class to do golden section line search.
GoldenSectionLineSearch(double, double, double) - Constructor for class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
GoldenSectionLineSearch(double, double, double, boolean) - Constructor for class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
GoldenSectionLineSearch(boolean) - Constructor for class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
GoldenSectionLineSearch(boolean, double, double, double) - Constructor for class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
GoldenSectionLineSearch(boolean, double, double, double, boolean) - Constructor for class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
goodTuringSmoothedCounter(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a Good-Turing smoothed Distribution from the given counter.
goodTuringWithExplicitUnknown(Counter<E>, E) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a Good-Turing smoothed Distribution from the given counter without creating any reserved mass-- instead, the special object UNK in the counter is assumed to be the count of "UNSEEN" items.
grad - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
gradList - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
gradPerturbed - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
greekifyNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
GREEN - Static variable in class edu.stanford.nlp.classify.ClassifierExample
 
GREEN - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 

H

handle(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.LogRecordHandler
Handle a log Record, either as a filter or by producing a side effect.
handle(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Handle a log Record, either as a filter or by producing a side effect.
handle(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
Handle a log Record, either as a filter or by producing a side effect.
handle(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Handle a log Record, either as a filter or by producing a side effect.
handler(LogRecordHandler, LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a handler to as a child of an existing parent
has(Class<KEY>) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Returns true if the map contains the given key.
has(Class<KEY>) - Method in interface edu.stanford.nlp.util.TypesafeMap
Returns true if the map contains the given key.
HasCategory - Interface in edu.stanford.nlp.ling
Something that implements the HasCategory interface knows about categories.
HasContext - Interface in edu.stanford.nlp.ling
 
HasEvaluators - Interface in edu.stanford.nlp.optimization
Indicates that an minimizer supports evaluation periodically
HASH_MAP_FACTORY - Static variable in class edu.stanford.nlp.util.MapFactory
 
HASH_SET_FACTORY - Static variable in class edu.stanford.nlp.util.CollectionFactory
 
HashableCoreMap - Class in edu.stanford.nlp.util
An extension of ArrayCoreMap with an immutable set of key,value pairs that is used for equality and hashcode comparisons.
HashableCoreMap(Map<Class<? extends TypesafeMap.Key<CoreMap, ?>>, Object>) - Constructor for class edu.stanford.nlp.util.HashableCoreMap
Creates an instance of HashableCoreMap with initial key,value pairs for the immutable, hashable keys as provided in the given map.
HashableCoreMap(ArrayCoreMap, Set<Class<? extends TypesafeMap.Key<CoreMap, ?>>>) - Constructor for class edu.stanford.nlp.util.HashableCoreMap
Creates an instance by copying values from the given other CoreMap, using the values it associates with the given set of hashkeys for the immutable, hashable keys used by hashcode and equals.
HashableCoreMap.HashableCoreMapException - Exception in edu.stanford.nlp.util
An exception thrown when attempting to change the value associated with an (immutable) hash key in a HashableCoreMap.
HashableCoreMap.HashableCoreMapException(String) - Constructor for exception edu.stanford.nlp.util.HashableCoreMap.HashableCoreMapException
 
hashCode() - Method in class edu.stanford.nlp.ling.BasicDatum
 
hashCode() - Method in class edu.stanford.nlp.ling.RVFDatum
hashCode() - Method in class edu.stanford.nlp.ling.ValueLabel
Return the hashCode of the String value providing there is one.
hashCode() - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
hashCode() - Method in class edu.stanford.nlp.ling.WordTag
 
hashCode() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns a hashCode which is the underlying Map's hashCode.
hashCode() - Method in class edu.stanford.nlp.stats.Distribution
 
hashCode() - Method in class edu.stanford.nlp.stats.IntCounter
 
hashCode() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
hashCode() - Method in class edu.stanford.nlp.util.ArrayCoreMap
Returns a composite hashCode over all the keys and values currently stored in the map.
hashCode() - Method in class edu.stanford.nlp.util.ArrayMap
 
hashCode() - Method in class edu.stanford.nlp.util.HashableCoreMap
Provides a hash code based on the immutable keys and values provided to the constructor.
hashCode() - Method in class edu.stanford.nlp.util.Interval
 
hashCode() - Method in class edu.stanford.nlp.util.IntPair
 
hashCode() - Method in class edu.stanford.nlp.util.IntTuple
 
hashCode() - Method in class edu.stanford.nlp.util.MetaClass.ClassFactory
 
hashCode() - Method in class edu.stanford.nlp.util.MetaClass
 
hashCode() - Method in class edu.stanford.nlp.util.MutableDouble
 
hashCode() - Method in class edu.stanford.nlp.util.MutableInteger
 
hashCode() - Method in class edu.stanford.nlp.util.Pair
 
hashCode() - Method in class edu.stanford.nlp.util.ScoredComparator
Return the hashCode: there are only two distinct comparators by equals().
hashCode() - Method in class edu.stanford.nlp.util.Triple
 
hashCodeCache - Variable in class edu.stanford.nlp.util.ArrayMap
 
HashIndex<E> - Class in edu.stanford.nlp.util
An Index is a collection that maps between an Object vocabulary and a contiguous non-negative integer index series beginning (inclusively) at 0.
HashIndex() - Constructor for class edu.stanford.nlp.util.HashIndex
Creates a new Index.
HashIndex(int) - Constructor for class edu.stanford.nlp.util.HashIndex
Creates a new Index.
HashIndex(Collection<? extends E>) - Constructor for class edu.stanford.nlp.util.HashIndex
Creates a new Index and adds every member of c to it.
HashIndex(Index<? extends E>) - Constructor for class edu.stanford.nlp.util.HashIndex
 
hashMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns a HashMap.
hashSetFactory() - Static method in class edu.stanford.nlp.util.CollectionFactory
 
HasIndex - Interface in edu.stanford.nlp.ling
 
hasInfinite(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
HasInitial - Interface in edu.stanford.nlp.optimization
Indicates that a function has a method for supplying an intitial value.
HasInterval<E extends Comparable<E>> - Interface in edu.stanford.nlp.util
HasInterval interface
hasNaN(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
hasNaN(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
hasNewVals - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
hasNext() - Method in class edu.stanford.nlp.objectbank.LineIterator
 
hasNext() - Method in class edu.stanford.nlp.util.AbstractIterator
 
hasNext() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
hasNext() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns true if the priority queue is non-empty
HasOffset - Interface in edu.stanford.nlp.ling
Something that implements the HasOffset interface bears a offset reference to the original text
HasTag - Interface in edu.stanford.nlp.ling
Something that implements the HasTag interface knows about part-of-speech tags.
HasWord - Interface in edu.stanford.nlp.ling
Something that implements the HasWord interface knows about words.
HdotV - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
HdotVAt(double[], double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
HdotVAt will return the hessian vector product H.v at the point x for a batchSize subset of the data There are several ways to perform this calculation, as of now Finite Difference, and Algorithmic Differentiation are the methods that have been used.
HdotVAt(double[], double[], double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
HdotVAt(double[], double[]) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
head() - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
heldOutSetSigma(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
heldOutSetSigma(GeneralDataset<L, F>, Scorer<L>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
heldOutSetSigma(GeneralDataset<L, F>, GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
heldOutSetSigma(GeneralDataset<L, F>, GeneralDataset<L, F>, Scorer<L>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
heldOutSetSigma(GeneralDataset<L, F>, GeneralDataset<L, F>, LineSearcher) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
heldOutSetSigma(GeneralDataset<L, F>, GeneralDataset<L, F>, Scorer<L>, LineSearcher) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the sigma parameter to a value that optimizes the held-out score given by scorer.
hide() - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
Hides all of these channels.
hideAll() - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Show none of the channels
hideAllChannels() - Static method in class edu.stanford.nlp.util.logging.Redwood
Hide all channels.
hideChannels(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Hide multiple channels.
hideChannels(Object[]) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Hide the following channels.
hideOnlyChannels(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Hide multiple channels.
hIndex(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Calculate h-Index (Hirsch, 2005) of an author.
howLong() - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
Return the time in seconds since this class was created.
HUBER_PRIOR - Static variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
hybridCutoffIteration - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
HybridMinimizer - Class in edu.stanford.nlp.optimization
Hybrid Minimizer is set up as a combination of two minimizers.
HybridMinimizer(Minimizer<DiffFunction>, Minimizer<DiffFunction>, int) - Constructor for class edu.stanford.nlp.optimization.HybridMinimizer
 
hypergeometric(int, int, int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Find a hypergeometric distribution.

I

IDENTITY_HASH_MAP_FACTORY - Static variable in class edu.stanford.nlp.util.MapFactory
 
IdentityFunction<X> - Class in edu.stanford.nlp.objectbank
An Identity function that returns its argument.
IdentityFunction() - Constructor for class edu.stanford.nlp.objectbank.IdentityFunction
 
identityHashMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns an IdentityHashMap.
ifrf - Variable in class edu.stanford.nlp.objectbank.ObjectBank
 
includesBegin() - Method in class edu.stanford.nlp.util.Interval
Returns whether the start endpoint is included in the interval
includesEnd() - Method in class edu.stanford.nlp.util.Interval
Returns whether the end endpoint is included in the interval
incrementBatch(int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
incrementBatch will shift the curElement variable to mark the next batch.
incrementCount(E, double) - Method in class edu.stanford.nlp.stats.AbstractCounter
 
incrementCount(E) - Method in class edu.stanford.nlp.stats.AbstractCounter
 
incrementCount(E, double) - Method in class edu.stanford.nlp.stats.ClassicCounter
Increments the count for the given key by the given value.
incrementCount(E) - Method in class edu.stanford.nlp.stats.ClassicCounter
Increments the count for this key by 1.0.
incrementCount(E, double) - Method in interface edu.stanford.nlp.stats.Counter
Increments the count for the given key by the given value.
incrementCount(E) - Method in interface edu.stanford.nlp.stats.Counter
Increments the count for this key by 1.0.
incrementCount(E, int) - Method in class edu.stanford.nlp.stats.IntCounter
Adds the given count to the current count for the given key.
incrementCount(E) - Method in class edu.stanford.nlp.stats.IntCounter
Adds 1 to the count for the given key.
incrementCount(E, double) - Method in class edu.stanford.nlp.stats.IntCounter
 
incrementCount(K1, K2) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
incrementCount(K1, K2, double) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
incrementCount(K1, K2) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
incrementCount(K1, K2, double) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
incrementCounts(Collection<E>, int) - Method in class edu.stanford.nlp.stats.IntCounter
Adds the given count to the current counts for each of the given keys.
incrementCounts(Collection<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Adds 1 to the counts for each of the given keys.
incrementRandom(int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
incValue(int) - Method in class edu.stanford.nlp.util.MutableInteger
Add the argument to the value of this integer.
index() - Method in class edu.stanford.nlp.ling.CoreLabel
index() - Method in interface edu.stanford.nlp.ling.HasIndex
 
Index<E> - Interface in edu.stanford.nlp.util
Minimalist interface for implementations of Index.
indexOf(int, int) - Method in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
indexOf(int, int) - Method in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
indexOf(int) - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
indexOf(int, int, int) - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
indexOf(int, int) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
indexOf(int, int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
indexOf(E) - Method in class edu.stanford.nlp.util.HashIndex
Returns the integer index of the Object in the Index or -1 if the Object is not already in the Index.
indexOf(E, boolean) - Method in class edu.stanford.nlp.util.HashIndex
Takes an Object and returns the integer index of the Object, perhaps adding it to the index first.
indexOf(E) - Method in interface edu.stanford.nlp.util.Index
Returns the integer index of the Object in the Index or -1 if the Object is not already in the Index.
indexOf(E, boolean) - Method in interface edu.stanford.nlp.util.Index
Takes an Object and returns the integer index of the Object, perhaps adding it to the index first.
indices(Collection<E>) - Method in class edu.stanford.nlp.util.HashIndex
Returns the index of each elem in a List.
inferenceType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
info - Variable in class edu.stanford.nlp.util.logging.OutputHandler
The current track info; used to avoid trackStack.peek() calls
infoFile - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
init(List<Pair<Double, Integer>>) - Method in class edu.stanford.nlp.classify.PRCurve
 
init(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
init(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
init(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.SQNMinimizer
 
init(AbstractStochasticCachingDiffUpdateFunction) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
init(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
initial() - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
use a random starting point uniform -1 1
initial() - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
initial() - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
initial() - Method in interface edu.stanford.nlp.optimization.HasInitial
Returns the intitial point in the domain (but not necessarily a feasible one).
initialGain - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
initialize(int) - Method in class edu.stanford.nlp.classify.Dataset
 
initialize(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
This method takes care of resetting values of the dataset such that it is empty with an initial capacity of numDatums Should be accessed only by appropriate methods within the class, such as clear(), which take care of other parts of the emptying of data
initialize(int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
initialWeights - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
initMC(ArrayList<Triple<Double, Integer, Integer>>) - Method in class edu.stanford.nlp.classify.PRCurve
 
initMC(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>) - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
initViterbi - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
innaPPAttach - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
innerProduct(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
innerProduct(float[], float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
inputEncoding - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
IntCounter<E> - Class in edu.stanford.nlp.stats
A specialized kind of hash table (or map) for storing numeric counts for objects.
IntCounter() - Constructor for class edu.stanford.nlp.stats.IntCounter
Constructs a new (empty) Counter.
IntCounter(MapFactory<E, MutableInteger>) - Constructor for class edu.stanford.nlp.stats.IntCounter
Pass in a MapFactory and the map it vends will back your counter.
IntCounter(IntCounter<E>) - Constructor for class edu.stanford.nlp.stats.IntCounter
Constructs a new Counter with the contents of the given Counter.
interimOutputFreq - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
intern - Variable in class edu.stanford.nlp.classify.LinearClassifier
 
intern - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
intern(T) - Method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
Returns a unique object o' that .equals the argument o.
intern(T) - Method in class edu.stanford.nlp.util.Interner
Returns a unique object o' that .equals the argument o.
intern2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
internAll(Set<T>) - Method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
Returns a Set such that each element in the returned set is a unique object e' that .equals the corresponding element e in the original set.
internAll(Set<T>) - Method in class edu.stanford.nlp.util.Interner
Returns a Set such that each element in the returned set is a unique object e' that .equals the corresponding element e in the original set.
internedStringPair(String, String) - Static method in class edu.stanford.nlp.util.Pair
Returns an MutableInternedPair where the Strings have been interned.
interner - Static variable in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
Interner<T> - Class in edu.stanford.nlp.util
For interning (canonicalizing) things.
Interner() - Constructor for class edu.stanford.nlp.util.Interner
 
interner - Static variable in class edu.stanford.nlp.util.Interner
 
intersect(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Returns interval that is the intersection of this and the other interval Returns null if intersect is null
intersection(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a counter that is the intersection of c1 and c2.
intersection(Set<T>, Set<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
intersection(Set<E>, Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns the intersection of sets s1 and s2.
intersects(Set<E>, Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns true if there is at least element that is in both s1 and s2.
Interval<E extends Comparable<E>> - Class in edu.stanford.nlp.util
Represents a interval of a generic type E that is comparable.
Interval(E, E, int) - Constructor for class edu.stanford.nlp.util.Interval
 
Interval.RelType - Enum in edu.stanford.nlp.util
RelType gives the basic types of relations between two intervals
INTERVAL_OPEN_BEGIN - Static variable in class edu.stanford.nlp.util.Interval
Flag indicating that an interval's begin point is not inclusive (by default, begin points are inclusive)
INTERVAL_OPEN_END - Static variable in class edu.stanford.nlp.util.Interval
Flag indicating that an interval's end point is not inclusive (by default, begin points are inclusive)
IntPair - Class in edu.stanford.nlp.util
 
IntPair() - Constructor for class edu.stanford.nlp.util.IntPair
 
IntPair(int, int) - Constructor for class edu.stanford.nlp.util.IntPair
 
intPow(int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Exponentiation like we learned in grade school: multiply b by itself e times.
intPow(float, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Exponentiation like we learned in grade school: multiply b by itself e times.
intPow(double, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Exponentiation like we learned in grade school: multiply b by itself e times.
IntQuadruple - Class in edu.stanford.nlp.util
 
IntQuadruple() - Constructor for class edu.stanford.nlp.util.IntQuadruple
 
IntQuadruple(int, int, int, int) - Constructor for class edu.stanford.nlp.util.IntQuadruple
 
IntTriple - Class in edu.stanford.nlp.util
 
IntTriple() - Constructor for class edu.stanford.nlp.util.IntTriple
 
IntTriple(int, int, int) - Constructor for class edu.stanford.nlp.util.IntTriple
 
IntTuple - Class in edu.stanford.nlp.util
A tuple of int.
IntTuple(int[]) - Constructor for class edu.stanford.nlp.util.IntTuple
 
IntTuple(int) - Constructor for class edu.stanford.nlp.util.IntTuple
 
IntUni - Class in edu.stanford.nlp.util
Just a single integer
IntUni() - Constructor for class edu.stanford.nlp.util.IntUni
 
IntUni(int) - Constructor for class edu.stanford.nlp.util.IntUni
 
intValue() - Method in class edu.stanford.nlp.math.DoubleAD
 
intValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
intValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
iobTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
iobWrapper - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
IOUtils - Class in edu.stanford.nlp.io
Helper Class for storing serialized objects to disk.
isAcronym(String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a String the method uses Regex to check if the String looks like an acronym
isAlpha(String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a String the method uses Regex to check if the String only contains alphabet characters
isAlphanumeric(String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a String the method uses Regex to check if the String only contains alphanumeric characters
isCapitalized(String) - Static method in class edu.stanford.nlp.util.StringUtils
Check if a string begins with an uppercase.
isCloseTo(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
 
isDangerous(double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns true if the argument is a "dangerous" double to have around, namely one that is infinite, NaN or zero.
isEmpty() - Method in class edu.stanford.nlp.objectbank.ObjectBank
 
isEmpty() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns whether a Counter has no keys in it.
isEmpty() - Method in class edu.stanford.nlp.stats.IntCounter
 
isEmpty() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
isEmpty() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
isEmpty() - Method in class edu.stanford.nlp.util.ArrayMap
 
isEmpty() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Checks if the queue is empty.
isIntervalComparable(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Checks whether this interval is comparable with another interval comes before or after
isLocked() - Method in class edu.stanford.nlp.util.HashIndex
Queries the Index for whether it's locked or not.
isLocked() - Method in interface edu.stanford.nlp.util.Index
Queries the Index for whether it's locked or not.
isNumeric(String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a String the method uses Regex to check if the String only contains numeric characters
isPunct(String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a String the method uses Regex to check if the String only contains punctuation characters
isSubList(List<T>, List<? super T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns true iff l1 is a sublist of l (i.e., every member of l1 is in l, and for every e1 < e2 in l1, there is an e1 < e2 occurrence in l).
isVeryDangerous(double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns true if the argument is a "very dangerous" double to have around, namely one that is infinite or NaN.
ITALIC - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
iterator() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
iterator() - Method in class edu.stanford.nlp.classify.RVFDataset
iterator() - Method in class edu.stanford.nlp.objectbank.ObjectBank
 
iterator() - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Returns an Iterator over the input sources in the underlying Collection.
iterator() - Method in class edu.stanford.nlp.stats.ClassicCounter
This is a shorthand for keySet.iterator().
iterator() - Method in class edu.stanford.nlp.stats.IntCounter
 
iterator() - Method in class edu.stanford.nlp.util.ArrayIterable
 
iterator() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
iterator() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
iterator() - Method in class edu.stanford.nlp.util.HashIndex
Returns an iterator over the elements of the collection.
iterator() - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
IteratorFromReaderFactory<T> - Interface in edu.stanford.nlp.objectbank
An IteratorFromReaderFactory is used to convert a java.io.Reader into an Iterator over the Objects of type T represented by the text in the java.io.Reader.
iterFilesRecursive(File) - Static method in class edu.stanford.nlp.io.IOUtils
Iterate over all the files in the directory, recursively.
iterFilesRecursive(File, String) - Static method in class edu.stanford.nlp.io.IOUtils
Iterate over all the files in the directory, recursively.
iterFilesRecursive(File, Pattern) - Static method in class edu.stanford.nlp.io.IOUtils
Iterate over all the files in the directory, recursively.

J

jaccardCoefficient(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the Jaccard Coefficient of the two counters.
jensenShannonDivergence(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the Jensen Shannon divergence (information radius) between a and b, defined as the average of the kl divergences from a to b and from b to a.
jensenShannonDivergence(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Calculates the Jensen-Shannon divergence between the two counters.
JL - Static variable in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
join(List<? extends E>, String, Function<E, String>, int, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
join(Iterable<X>, String) - Static method in class edu.stanford.nlp.util.StringUtils
Joins each elem in the Collection with the given glue.
join(Object[], String) - Static method in class edu.stanford.nlp.util.StringUtils
Joins each elem in the array with the given glue.
join(Iterable<?>) - Static method in class edu.stanford.nlp.util.StringUtils
Joins elems with a space.
join(Object[]) - Static method in class edu.stanford.nlp.util.StringUtils
Joins elements with a space.
joinWithOriginalWhiteSpace(List<CoreLabel>) - Static method in class edu.stanford.nlp.util.StringUtils
Joins all the tokens together (more or less) according to their original whitespace.
joinWords(Iterable<? extends HasWord>, String) - Static method in class edu.stanford.nlp.util.StringUtils
 
joinWords(List<? extends HasWord>, String, int, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
justificationOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
justificationOf(RVFDatum<L, F>, PrintWriter) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
justificationOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
justificationOf(Datum<L, F>, PrintWriter, Function<F, T>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
justificationOf(Datum<L, F>, PrintWriter, Function<F, T>, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Print all features active for a particular datum and the weight that the classifier assigns to each class for those features.
justificationOf(Datum<L, F>, PrintWriter) - Method in class edu.stanford.nlp.classify.LinearClassifier
Print all features active for a particular datum and the weight that the classifier assigns to each class for those features.
justificationOf(Datum<L, F>, PrintWriter, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Print all features active for a particular datum and the weight that the classifier assigns to each class for those features.
justificationOf(Counter<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
justificationOf(Collection<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
returns the weights assigned by the classifier to each feature
justify - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 

K

k - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
kBest - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
keepAllWhitespaces - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
Keep all the whitespace words in testFile when printing out answers.
keepEnglishWhitespaces - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
Keep the whitespace between English words in testFile when printing out answers.
keepInMemory(boolean) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Tells the ObjectBank to store all of its contents in memory so that it doesn't have to be recomputed each time you iterate through it.
keepOBInMemory - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
keysAbove(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns the set of keys whose counts are at or above the given threshold.
keysAbove(int) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the set of keys whose counts are at or above the given threshold.
keysAt(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns the set of keys that have exactly the given count.
keysAt(int) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the set of keys that have exactly the given count.
keysBelow(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns the set of keys whose counts are at or below the given threshold.
keysBelow(int) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the set of keys whose counts are at or below the given threshold.
keySet() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns the Set of keys in this counter.
keySet() - Method in interface edu.stanford.nlp.stats.Counter
Returns the Set of keys in this counter.
keySet() - Method in class edu.stanford.nlp.stats.Distribution
 
keySet() - Method in class edu.stanford.nlp.stats.IntCounter
 
keySet() - Method in class edu.stanford.nlp.util.ArrayCoreMap
Collection of keys currently held in this map.
keySet() - Method in interface edu.stanford.nlp.util.TypesafeMap
Collection of keys currently held in this map.
klDivergence(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
klDivergence(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Calculates the KL divergence between the two counters.

L

L1Norm(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
L1Norm(C) - Static method in class edu.stanford.nlp.stats.Counters
Return the L1 norm of a counter.
L1normalize(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
l1reg - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
L2Norm(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
L2Norm(C) - Static method in class edu.stanford.nlp.stats.Counters
Return the l2 norm (Euclidean vector length) of a Counter.
L2Normalize(C) - Static method in class edu.stanford.nlp.stats.Counters
L2 normalize a counter.
L2NormalizeInPlace(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
L2 normalize a counter in place.
label() - Method in class edu.stanford.nlp.ling.BasicDatum
Returns the first label for this Datum, or null if none have been set.
Label - Interface in edu.stanford.nlp.ling
Something that implements the Label interface can act as a constituent, node, or word label with linguistic attributes.
label() - Method in interface edu.stanford.nlp.ling.Labeled
Returns the primary label for this Object, or null if none have been set.
label() - Method in class edu.stanford.nlp.ling.RVFDatum
 
Labeled<E> - Interface in edu.stanford.nlp.ling
Interface for Objects that have a label, whose label is an Object.
labelFactory() - Method in class edu.stanford.nlp.ling.CoreLabel
Returns a factory that makes labels of the exact same type as this one.
labelFactory() - Method in interface edu.stanford.nlp.ling.Label
Returns a factory that makes labels of the exact same type as this one.
LabelFactory - Interface in edu.stanford.nlp.ling
A LabelFactory object acts as a factory for creating objects of class Label, or some descendant class.
labelFactory() - Method in class edu.stanford.nlp.ling.StringLabel
Return a factory for this kind of label (i.e., StringLabel).
labelFactory() - Method in class edu.stanford.nlp.ling.TaggedWord
Return a factory for this kind of label (i.e., TaggedWord).
labelFactory() - Method in class edu.stanford.nlp.ling.ValueLabel
Returns a factory that makes Labels of the appropriate sort.
labelFactory() - Method in class edu.stanford.nlp.ling.Word
Return a factory for this kind of label (i.e., Word).
labelFactory() - Method in class edu.stanford.nlp.ling.WordLemmaTag
Return a factory for this kind of label (i.e., TaggedWord).
labelFactory() - Method in class edu.stanford.nlp.ling.WordTag
Return a factory for this kind of label (i.e., TaggedWord).
labelIndex - Variable in class edu.stanford.nlp.classify.GeneralDataset
 
labelIndex() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
labelIndex() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
labelIndex - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
labelIterator() - Method in class edu.stanford.nlp.classify.GeneralDataset
Returns an iterator over the class labels of the Dataset
labels - Variable in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
labels() - Method in interface edu.stanford.nlp.classify.Classifier
 
labels - Variable in class edu.stanford.nlp.classify.GeneralDataset
 
labels() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
labels - Variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
labels - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
labels() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
labels() - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
labels() - Method in class edu.stanford.nlp.ling.BasicDatum
Returns the complete List of labels for this Datum, which may be empty.
labels() - Method in interface edu.stanford.nlp.ling.Labeled
Returns the complete list of labels for this Object, which may be empty.
labels() - Method in class edu.stanford.nlp.ling.RVFDatum
 
lam - Variable in class edu.stanford.nlp.optimization.SMDMinimizer
 
lambda - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
laplaceSmoothedDistribution(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Distribution
Creates an Laplace smoothed Distribution from the given counter, ie adds one count to every item, including unseen ones, and divides by the total count.
laplaceSmoothedDistribution(Counter<E>, int, double) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a smoothed Distribution using Lidstone's law, ie adds lambda (typically between 0 and 1) to every item, including unseen ones, and divides by the total count.
laplaceWithExplicitUnknown(Counter<E>, double, E) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a smoothed Distribution with Laplace smoothing, but assumes an explicit count of "UNKNOWN" items.
largeChSegFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
lastBatch - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastBatchSize - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastDerivative() - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastElement - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastNameList - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
lastValue() - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
lastValue() - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastVBatch - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
lastXBatch - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
leftMargin - Variable in class edu.stanford.nlp.util.logging.OutputHandler
The length of the left margin in which to print channel information.
lemma() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the lemma of the label (or null if none).
lemma() - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
lemma(String, String) - Method in class edu.stanford.nlp.process.Morphology
 
lemma(String, String, boolean) - Method in class edu.stanford.nlp.process.Morphology
 
LEMMA_LABEL - Static variable in class edu.stanford.nlp.ling.WordLemmaTagFactory
 
lemmaStatic(String, String, boolean) - Static method in class edu.stanford.nlp.process.Morphology
 
lemmaStaticSynchronized(String, String, boolean) - Static method in class edu.stanford.nlp.process.Morphology
 
lemmatize(WordTag) - Method in class edu.stanford.nlp.process.Morphology
Lemmatize returning a WordLemmaTag .
lemmatizeStatic(WordTag) - Static method in class edu.stanford.nlp.process.Morphology
 
length() - Method in class edu.stanford.nlp.util.IntTuple
 
lgamma(double) - Static method in class edu.stanford.nlp.math.SloppyMath
 
LinearClassifier<L,F> - Class in edu.stanford.nlp.classify
Implements a multiclass linear classifier.
LinearClassifier(double[][], Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.LinearClassifier
 
LinearClassifier(double[][], Index<F>, Index<L>, double[]) - Constructor for class edu.stanford.nlp.classify.LinearClassifier
 
LinearClassifier(double[], Index<Pair<F, L>>) - Constructor for class edu.stanford.nlp.classify.LinearClassifier
 
LinearClassifier(Counter<? extends Pair<F, L>>) - Constructor for class edu.stanford.nlp.classify.LinearClassifier
 
LinearClassifier(Counter<? extends Pair<F, L>>, Counter<L>) - Constructor for class edu.stanford.nlp.classify.LinearClassifier
 
LinearClassifierFactory<L,F> - Class in edu.stanford.nlp.classify
Builds various types of linear classifiers, with functionality for setting objective function, optimization method, and other parameters.
LinearClassifierFactory() - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(boolean) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>, boolean) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>, double, boolean) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(double, boolean, double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>, double, boolean, double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>, double, boolean, int, double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(double, boolean, int, double, double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(double, boolean, int, double, double, int) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory(Minimizer<DiffFunction>, double, boolean, int, double, double) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
Create a factory that builds linear classifiers from training data.
LinearClassifierFactory(Minimizer<DiffFunction>, double, boolean, LogPrior) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory
 
LinearClassifierFactory.LinearClassifierCreator<L,F> - Class in edu.stanford.nlp.classify
 
LinearClassifierFactory.LinearClassifierCreator(LogConditionalObjectiveFunction, Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory.LinearClassifierCreator
 
LinearClassifierFactory.LinearClassifierCreator(Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.LinearClassifierFactory.LinearClassifierCreator
 
linearCombination(Counter<E>, double, Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns a Counter which is a weighted average of c1 and c2.
lineCount(File) - Static method in class edu.stanford.nlp.io.IOUtils
 
LineIterator<X> - Class in edu.stanford.nlp.objectbank
An Iterator that returns a line of a file at a time.
LineIterator(Reader) - Constructor for class edu.stanford.nlp.objectbank.LineIterator
 
LineIterator(Reader, Function<String, X>) - Constructor for class edu.stanford.nlp.objectbank.LineIterator
 
LineIterator.LineIteratorFactory<X> - Class in edu.stanford.nlp.objectbank
 
LineIterator.LineIteratorFactory() - Constructor for class edu.stanford.nlp.objectbank.LineIterator.LineIteratorFactory
 
LineIterator.LineIteratorFactory(Function<String, X>) - Constructor for class edu.stanford.nlp.objectbank.LineIterator.LineIteratorFactory
 
LineSearcher - Interface in edu.stanford.nlp.optimization
The interface for one variable function minimizers.
linesFromFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns the contents of a file as a list of strings.
linesFromFile(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns the contents of a file as a list of strings.
LINKED_LIST_FACTORY - Static variable in class edu.stanford.nlp.util.CollectionFactory
 
linkedHashMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns an LinkedHashMap.
linkedListFactory() - Static method in class edu.stanford.nlp.util.CollectionFactory
 
listToFile(List<double[]>, String) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
load2DCounter(String, Class<T1>, Class<T2>) - Static method in class edu.stanford.nlp.stats.Counters
 
load2DMatrixFromFile(String) - Static method in class edu.stanford.nlp.math.ArrayMath
 
loadAuxClassifier - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
loadByReflection(String, Object...) - Static method in class edu.stanford.nlp.util.ReflectionLoading
You can use this as follows:
String s = ReflectionLoading.loadByReflection("java.lang.String", "foo");
String s = ReflectionLoading.loadByReflection("java.lang.String");
Note that this uses generics for convenience, but this does nothing for compile-time error checking.
loadClassifier - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
loadCollection(String, Class<T>, CollectionFactory<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
loadCollection(File, Class<T>, CollectionFactory<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
loadCollection(String, Class<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Adds the items from the file to the collection.
loadCollection(File, Class<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Adds the items from the file to the collection.
loadCounter(String, Class<E>) - Static method in class edu.stanford.nlp.stats.Counters
Loads a Counter from a text file.
loadDatasetsDir - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
loadFromFilename(String) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Given the path to a file representing the text based serialization of a Linear Classifier, reconstitutes and returns that LinearClassifier.
loadFromFilename(String) - Static method in class edu.stanford.nlp.util.HashIndex
 
loadFromReader(BufferedReader) - Static method in class edu.stanford.nlp.util.HashIndex
This is the analogue of loadFromFilename, and is intended to be included in a routine that unpacks a text-serialized form of an object that incorporates an Index.
loadIncInto2DCounter(String, Class<T1>, Class<T2>, TwoDimensionalCounterInterface<T1, T2>) - Static method in class edu.stanford.nlp.stats.Counters
 
loadIntCounter(String, Class<E>) - Static method in class edu.stanford.nlp.stats.Counters
Loads a Counter from a text file.
loadInto2DCounter(String, Class<T1>, Class<T2>, TwoDimensionalCounter<T1, T2>) - Static method in class edu.stanford.nlp.stats.Counters
 
loadJarClassifier - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
loadProcessedData - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
loadTextClassifier - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
lock() - Method in class edu.stanford.nlp.util.HashIndex
Locks the Index.
lock() - Method in interface edu.stanford.nlp.util.Index
Locks the Index.
log(DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
log(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
log(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Convenience method for log to a different base
log(Object) - Static method in class edu.stanford.nlp.util.logging.PrettyLogger
Pretty log an object.
log(String, Object) - Static method in class edu.stanford.nlp.util.logging.PrettyLogger
Pretty log an object along with its description.
log(Redwood.RedwoodChannels, Object) - Static method in class edu.stanford.nlp.util.logging.PrettyLogger
Pretty log an object.
log(Redwood.RedwoodChannels, String, Object) - Static method in class edu.stanford.nlp.util.logging.PrettyLogger
Pretty log an object.
log(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Log a message.
log(Object) - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
Log a message to the channels specified in this RedwoodChannels object.
log(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
logAdd(float, float) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the log of the sum of two numbers, which are themselves input in log form.
logAdd(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the log of the sum of two numbers, which are themselves input in log form.
LogConditionalEqConstraintFunction - Class in edu.stanford.nlp.classify
Maximizes the conditional likelihood with a given prior.
LogConditionalEqConstraintFunction(int, int, int[][], int[]) - Constructor for class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
LogConditionalEqConstraintFunction(int, int, int[][], int[], double) - Constructor for class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
LogConditionalEqConstraintFunction(int, int, int[][], int[], int, double, double) - Constructor for class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
LogConditionalObjectiveFunction<L,F> - Class in edu.stanford.nlp.classify
Maximizes the conditional likelihood with a given prior.
LogConditionalObjectiveFunction(GeneralDataset<L, F>) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(GeneralDataset<L, F>, LogPrior) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(GeneralDataset<L, F>, float[], LogPrior) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(GeneralDataset<L, F>, LogPrior, boolean) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(Iterable<Datum<L, F>>, LogPrior, Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[], boolean) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[]) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[], LogPrior) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[], float[]) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[], float[], LogPrior) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], int[], int, double, double) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
LogConditionalObjectiveFunction(int, int, int[][], double[][], int[], int, double, double) - Constructor for class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
logf(String, Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
 
logf(String, Object...) - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
Log a printf-style formatted message to the channels specified in this RedwoodChannels object.
logf(String, Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
loggingClass(String) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Set a Java classname path to ignore when printing stack traces
loggingClass(Class<?>) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Set a Java class to ignore when printing stack traces
logIncrementCount(E, double) - Method in class edu.stanford.nlp.stats.AbstractCounter
 
logIncrementCount(E, double) - Method in class edu.stanford.nlp.stats.ClassicCounter
Increments the count stored in log space for this key by the given log-transformed value.
logIncrementCount(E, double) - Method in interface edu.stanford.nlp.stats.Counter
Increments the count stored in log space for this key by the given log-transformed value.
logInPlace(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
logInPlace(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
LogisticClassifier<L,F> - Class in edu.stanford.nlp.classify
A classifier for binary logistic regression problems.
LogisticClassifier(double[], Index<F>, L[]) - Constructor for class edu.stanford.nlp.classify.LogisticClassifier
 
LogisticClassifier(boolean) - Constructor for class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
LogisticClassifier(LogPrior) - Constructor for class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
LogisticClassifier(LogPrior, boolean) - Constructor for class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
LogisticClassifierFactory<L,F> - Class in edu.stanford.nlp.classify
 
LogisticClassifierFactory() - Constructor for class edu.stanford.nlp.classify.LogisticClassifierFactory
 
LogisticObjectiveFunction - Class in edu.stanford.nlp.classify
Maximizes the conditional likelihood with a given prior.
LogisticObjectiveFunction(int, int[][], int[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], int[], LogPrior) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], int[], float[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], int[], LogPrior, float[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], double[][], int[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], double[][], int[], LogPrior) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], double[][], int[], float[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
LogisticObjectiveFunction(int, int[][], double[][], int[], LogPrior, float[]) - Constructor for class edu.stanford.nlp.classify.LogisticObjectiveFunction
 
logLikelihood() - Method in class edu.stanford.nlp.classify.PRCurve
assuming the scores are probability of 1 given x
logNormalize(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Makes the values in this array sum to 1.0.
logNormalizeInPlace(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Transform log space values into a probability distribution in place.
logPrecision(int) - Method in class edu.stanford.nlp.classify.PRCurve
what is the precision at this recall if we look at the score as the probability of class 1 given x as if coming from logistic regression
LogPrior - Class in edu.stanford.nlp.classify
A Prior for functions.
LogPrior() - Constructor for class edu.stanford.nlp.classify.LogPrior
 
LogPrior(int) - Constructor for class edu.stanford.nlp.classify.LogPrior
 
LogPrior(LogPrior.LogPriorType) - Constructor for class edu.stanford.nlp.classify.LogPrior
 
LogPrior(int, double, double) - Constructor for class edu.stanford.nlp.classify.LogPrior
 
LogPrior(LogPrior.LogPriorType, double, double) - Constructor for class edu.stanford.nlp.classify.LogPrior
 
LogPrior(double[]) - Constructor for class edu.stanford.nlp.classify.LogPrior
IMPORTANT NOTE: This constructor allows non-uniform regularization, but it transforms the inputs C (like the machine learning people like) to sigma (like we NLP folks like).
LogPrior.LogPriorType - Enum in edu.stanford.nlp.classify
 
logProbabilityOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns a counter mapping from each class name to the log probability of that class for a certain example.
logProbabilityOf(int[]) - Method in class edu.stanford.nlp.classify.LinearClassifier
Given a datum's features, returns a counter mapping from each class name to the log probability of that class.
logProbabilityOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
logProbabilityOf(Datum<L, F>) - Method in interface edu.stanford.nlp.classify.ProbabilisticClassifier
 
logProbabilityOf(E) - Method in class edu.stanford.nlp.stats.Distribution
Returns the natural logarithm of the object's probability
logProbabilityOf(E) - Method in interface edu.stanford.nlp.stats.ProbabilityDistribution
 
LogRecordHandler - Class in edu.stanford.nlp.util.logging
A log message handler.
LogRecordHandler() - Constructor for class edu.stanford.nlp.util.logging.LogRecordHandler
 
logSum(DoubleAD[]) - Static method in class edu.stanford.nlp.math.ADMath
 
logSum(DoubleAD[], int, int) - Static method in class edu.stanford.nlp.math.ADMath
 
logSum(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the log of the sum of an array of numbers, which are themselves input in log form.
logSum(double[], int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the log of the portion between fromIndex, inclusive, and toIndex, exclusive, of an array of numbers, which are themselves input in log form.
logSum(double[], int, int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the log of the portion between fromIndex, inclusive, and toIndex, exclusive, of an array of numbers, which are themselves input in log form.
logSum(List<Double>) - Static method in class edu.stanford.nlp.math.ArrayMath
 
logSum(List<Double>, int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
logSum(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the log of the sum of an array of numbers, which are themselves input in log form.
logSum(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns ArrayMath.logSum of the values in this counter.
longestCommonContiguousSubstring(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Computes the longest common contiguous substring of s and t.
longestCommonSubstring(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Computes the longest common substring of s and t.
longValue() - Method in class edu.stanford.nlp.math.DoubleAD
 
longValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
longValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
lookingAt(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Say whether this regular expression can be found at the beginning of this String.
lookupShaper(String) - Static method in class edu.stanford.nlp.process.WordShapeClassifier
Look up a shaper by a short String name.
lowercaseNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
lowerNewgeneThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 

M

MAGENTA - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
main(String[]) - Static method in class edu.stanford.nlp.classify.ClassifierExample
 
main(String[]) - Static method in class edu.stanford.nlp.classify.ColumnDataClassifier
Runs the ColumnDataClassifier from the command-line.
main(String[]) - Static method in class edu.stanford.nlp.classify.CrossValidator
 
main(String[]) - Static method in class edu.stanford.nlp.classify.LogisticClassifier
 
main(String[]) - Static method in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
main(String[]) - Static method in class edu.stanford.nlp.classify.PRCurve
 
main(String[]) - Static method in class edu.stanford.nlp.classify.RVFDataset
 
main(String[]) - Static method in class edu.stanford.nlp.io.IOUtils
 
main(String[]) - Static method in class edu.stanford.nlp.ling.WordLemmaTag
 
main(String[]) - Static method in class edu.stanford.nlp.math.ArrayMath
For testing only.
main(String[]) - Static method in class edu.stanford.nlp.math.SloppyMath
Tests the hypergeometric distribution code, or other functions provided in this module.
main(String[]) - Static method in class edu.stanford.nlp.objectbank.LineIterator
 
main(String[]) - Static method in class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
main(String[]) - Static method in class edu.stanford.nlp.optimization.SGDMinimizer
 
main(String[]) - Static method in class edu.stanford.nlp.optimization.SMDMinimizer
 
main(String[]) - Static method in class edu.stanford.nlp.process.Morphology
Run the morphological analyzer.
main(String[]) - Static method in class edu.stanford.nlp.process.WordShapeClassifier
Usage: java edu.stanford.nlp.process.WordShapeClassifier [-wordShape name] string+
where name is an argument to lookupShaper.
main(String[]) - Static method in class edu.stanford.nlp.stats.Distribution
For internal testing purposes only.
main(String[]) - Static method in class edu.stanford.nlp.stats.SimpleGoodTuring
Like Sampson's SGT program, reads data from STDIN and writes results to STDOUT.
main(String[]) - Static method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
main(String[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
main(String[]) - Static method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
main(String[]) - Static method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
Test method: interns its arguments and says whether they == themselves.
main(String[]) - Static method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
main(String[]) - Static method in class edu.stanford.nlp.util.Interner
Test method: interns its arguments and says whether they == themselves.
main(String[]) - Static method in class edu.stanford.nlp.util.logging.Redwood
Various informal tests of Redwood functionality
main(String[]) - Static method in class edu.stanford.nlp.util.Sets
 
main(String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Tests the string edit distance function.
makeAsciiTable(Object[][], Object[], Object[], int, int, boolean) - Static method in class edu.stanford.nlp.util.StringUtils
Returns an text table containing the matrix of Strings passed in.
makeClassifier(GeneralDataset<String, String>) - Method in class edu.stanford.nlp.classify.ColumnDataClassifier
Creates a classifier from training data.
makeConsistent - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
makeDatumFromLine(String, int) - Method in class edu.stanford.nlp.classify.ColumnDataClassifier
Entry point for taking a String (formatted as a line of a TSV file) and translating it into a Datum of features.
makeHTMLTable(String[][], String[], String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Returns an HTML table containing the matrix of Strings passed in.
makeIntFromByte2(byte[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
makeIntFromByte4(byte[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
makeList(T...) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns a new List containing the given objects.
makePair(X, Y) - Static method in class edu.stanford.nlp.util.Pair
Returns a Pair constructed from X and Y.
makeStopLights(String, String) - Static method in class edu.stanford.nlp.classify.ClassifierExample
 
makeSvmLabelMap() - Method in class edu.stanford.nlp.classify.GeneralDataset
Maps our labels to labels that are compatible with svm_light
makeTriple(X, Y, Z) - Static method in class edu.stanford.nlp.util.Triple
Returns a Triple constructed from X, Y, and Z.
maleNameList - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
map - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
map - Variable in class edu.stanford.nlp.util.Interner
 
mapDataset(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
mapDataset(GeneralDataset<L, F>, Index<L2>, Map<L, L2>, L2) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
mapDatum(Datum<L, F>, Map<L, L2>, L2) - Static method in class edu.stanford.nlp.classify.GeneralDataset
 
MapFactory<K,V> - Class in edu.stanford.nlp.util
A factory class for vending different sorts of Maps.
MapFactory() - Constructor for class edu.stanford.nlp.util.MapFactory
 
mapStringToArray(String) - Static method in class edu.stanford.nlp.util.StringUtils
Takes a string of the form "x1=y1,x2=y2,..." such that each y is an integer and each x is a key.
mapStringToMap(String) - Static method in class edu.stanford.nlp.util.StringUtils
Takes a string of the form "x1=y1,x2=y2,..." and returns Map
markMasdar - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
markProperNN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
matches(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Say whether this regular expression matches this String.
max(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
max(Collection<Double>) - Static method in class edu.stanford.nlp.math.ArrayMath
 
max(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
max(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
max(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the smallest element of the matrix
max(int, int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
max() that works on three integers.
max(Collection<Integer>) - Static method in class edu.stanford.nlp.math.SloppyMath
 
max(int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the greater of two int values.
max(float, float) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the greater of two float values.
max(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the greater of two double values.
max(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the value of the maximum entry in this counter.
max() - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the largest count in this Counter.
max(E, E) - Static method in class edu.stanford.nlp.util.Interval
 
maxDocSize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
maxIterations - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
maxLeft - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
maxNGramLeng - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
maxRight - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
maxTime - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
maxTime - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
maxWaitTimeInMillis() - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ApproximateRepeatSemantics
 
maxWaitTimeInMillis() - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ExactRepeatSemantics
 
maxWaitTimeInMillis() - Method in interface edu.stanford.nlp.util.logging.RepeatedRecordHandler.RepeatSemantics
 
mean(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
mean(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the mean of all the counts (totalCount/size).
median(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
memory - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
memoryThrift - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
mergeList(List<? extends T>, Collection<M>, Function<M, Interval<Integer>>, Function<List<? extends T>, T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
mergeList(List<? extends T>, List<? extends HasInterval<Integer>>, Function<List<? extends T>, T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
mergeListWithSortedMatched(List<? extends T>, List<? extends HasInterval<Integer>>, Function<List<? extends T>, T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
mergeListWithSortedMatchedPreAggregated(List<? extends T>, List<? extends T>, Function<T, Interval<Integer>>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
mergeTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
message(int) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ApproximateRepeatSemantics
 
message(int) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ExactRepeatSemantics
 
message(int) - Method in interface edu.stanford.nlp.util.logging.RepeatedRecordHandler.RepeatSemantics
 
meta - Variable in class edu.stanford.nlp.optimization.SMDMinimizer
 
MetaClass - Class in edu.stanford.nlp.util
A meta class using Java's reflection library.
MetaClass(String) - Constructor for class edu.stanford.nlp.util.MetaClass
Creates a new MetaClass producing objects of the given type
MetaClass(Class<?>) - Constructor for class edu.stanford.nlp.util.MetaClass
Creates a new MetaClass producing objects of the given type
MetaClass.ClassCreationException - Exception in edu.stanford.nlp.util
 
MetaClass.ClassFactory<T> - Class in edu.stanford.nlp.util
 
MetaClass.ConstructorNotFoundException - Exception in edu.stanford.nlp.util
 
method - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
min(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
min(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
min(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
min(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the smallest element of the matrix
min(int, int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the minimum of three int values.
min(float, float) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the smaller of two float values.
min(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns the smaller of two double values.
min(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the value of the smallest entry in this counter.
min() - Method in class edu.stanford.nlp.stats.IntCounter
Finds and returns the smallest count in this Counter.
min(E, E) - Static method in class edu.stanford.nlp.util.Interval
 
minimize(DiffFunction, double, double[]) - Method in class edu.stanford.nlp.optimization.CGMinimizer
 
minimize(DiffFunction, double, double[], int) - Method in class edu.stanford.nlp.optimization.CGMinimizer
 
minimize(Function<Double, Double>, double, double, double) - Method in class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
minimize(Function<Double, Double>) - Method in class edu.stanford.nlp.optimization.GoldenSectionLineSearch
 
minimize(DiffFunction, double, double[]) - Method in class edu.stanford.nlp.optimization.HybridMinimizer
 
minimize(DiffFunction, double, double[], int) - Method in class edu.stanford.nlp.optimization.HybridMinimizer
 
minimize(Function<Double, Double>) - Method in interface edu.stanford.nlp.optimization.LineSearcher
Attempts to find an unconstrained minimum of the objective function starting at initial, within functionTolerance.
minimize(T, double, double[]) - Method in interface edu.stanford.nlp.optimization.Minimizer
Attempts to find an unconstrained minimum of the objective function starting at initial, within functionTolerance.
minimize(T, double, double[], int) - Method in interface edu.stanford.nlp.optimization.Minimizer
 
minimize(DiffFloatFunction, float, float[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
minimize(DiffFunction, double, double[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
minimize(DiffFunction, double, double[], int) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
minimize(DiffFunction, double, double[], int, QNMinimizer.QNInfo) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
minimize(DiffFunction, double, double[]) - Method in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
minimize(DiffFunction, double, double[], int) - Method in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
minimize(Function, double, double[]) - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
minimize(Function, double, double[]) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
minimize(Function, double, double[], int) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
minimize(Function, double, double[]) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
minimize(Function, double, double[], int) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
Minimizer<T extends Function> - Interface in edu.stanford.nlp.optimization
The interface for unconstrained function minimizers.
minLineCountForTrackNameReminder - Variable in class edu.stanford.nlp.util.logging.OutputHandler
Number of lines above which the closing brace of a track shows the name of the track
minus(DoubleAD, DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
minusConst(DoubleAD, double) - Static method in class edu.stanford.nlp.math.ADMath
 
minusEquals(DoubleAD) - Method in class edu.stanford.nlp.math.DoubleAD
 
minusEqualsConst(double) - Method in class edu.stanford.nlp.math.DoubleAD
 
mixedCaseMapFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
mkT2DArray(Class<?>, int[]) - Static method in class edu.stanford.nlp.util.ErasureUtils
 
mkTArray(Class<?>, int) - Static method in class edu.stanford.nlp.util.ErasureUtils
Makes an array based on klass, but casts it to be of type T[].
mode(Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns the mode in the Collection.
modes(Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Returns a list of all modes in the Collection.
monitorX(double[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
morphFeatureFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
Morphology - Class in edu.stanford.nlp.process
Morphology computes the base form of English words, by removing just inflections (not derivational morphology).
Morphology() - Constructor for class edu.stanford.nlp.process.Morphology
 
Morphology(Reader) - Constructor for class edu.stanford.nlp.process.Morphology
Process morphologically words from a Reader.
Morphology(Reader, int) - Constructor for class edu.stanford.nlp.process.Morphology
 
mu - Variable in class edu.stanford.nlp.optimization.SMDMinimizer
 
mult(DoubleAD, DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
multConst(DoubleAD, double) - Static method in class edu.stanford.nlp.math.ADMath
 
MultiClassAccuracyStats<L> - Class in edu.stanford.nlp.stats
 
MultiClassAccuracyStats() - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
MultiClassAccuracyStats(int) - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
MultiClassAccuracyStats(String) - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
MultiClassAccuracyStats(String, int) - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
MultiClassAccuracyStats(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>, String) - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
MultiClassAccuracyStats(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>, String, int) - Constructor for class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
multiply(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Scales the values in this array by c.
multiply(float[], float) - Static method in class edu.stanford.nlp.math.ArrayMath
Scales the values in this array by c.
multiplyInPlace(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Scales the values in this array by b.
multiplyInPlace(float[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Scales the values in this array by b.
multiplyInPlace(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Multiplies each value in target by the given multiplier, in place.
multiplyInto(double[], double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
MutableDouble - Class in edu.stanford.nlp.util
A class for Double objects that you can change.
MutableDouble() - Constructor for class edu.stanford.nlp.util.MutableDouble
 
MutableDouble(double) - Constructor for class edu.stanford.nlp.util.MutableDouble
 
MutableDouble(Number) - Constructor for class edu.stanford.nlp.util.MutableDouble
 
MutableInteger - Class in edu.stanford.nlp.util
A class for Integer objects that you can change.
MutableInteger() - Constructor for class edu.stanford.nlp.util.MutableInteger
 
MutableInteger(int) - Constructor for class edu.stanford.nlp.util.MutableInteger
 
mutex - Variable in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 

N

NaiveBayesClassifier<L,F> - Class in edu.stanford.nlp.classify
 
NaiveBayesClassifier(Counter<Pair<Pair<L, F>, Number>>, Counter<L>, Set<L>, Set<F>, boolean) - Constructor for class edu.stanford.nlp.classify.NaiveBayesClassifier
 
NaiveBayesClassifier(Counter<Pair<Pair<L, F>, Number>>, Counter<L>, Set<L>) - Constructor for class edu.stanford.nlp.classify.NaiveBayesClassifier
 
NaiveBayesClassifierFactory<L,F> - Class in edu.stanford.nlp.classify
 
NaiveBayesClassifierFactory() - Constructor for class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
NaiveBayesClassifierFactory(double, double, double, int, int) - Constructor for class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
NBLinearClassifierFactory<L,F> - Class in edu.stanford.nlp.classify
Provides a medium-weight implementation of Bernoulli (or binary) Naive Bayes via a linear classifier.
NBLinearClassifierFactory() - Constructor for class edu.stanford.nlp.classify.NBLinearClassifierFactory
Create a ClassifierFactory.
NBLinearClassifierFactory(double) - Constructor for class edu.stanford.nlp.classify.NBLinearClassifierFactory
Create a ClassifierFactory.
NBLinearClassifierFactory(double, boolean) - Constructor for class edu.stanford.nlp.classify.NBLinearClassifierFactory
Create a ClassifierFactory.
nChooseK(int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Computes n choose k in an efficient way.
neatExit() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Close tracks when the JVM shuts down.
ner() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the named entity class of the label (or null if none).
newArrayList() - Static method in class edu.stanford.nlp.util.Generics
 
newArrayList(int) - Static method in class edu.stanford.nlp.util.Generics
 
newArrayList(Collection<? extends E>) - Static method in class edu.stanford.nlp.util.Generics
 
newBinaryHeapPriorityQueue() - Static method in class edu.stanford.nlp.util.Generics
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.ArrayListFactory
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.HashSetFactory
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.LinkedListFactory
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.SizedArrayListFactory
 
newCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.TreeSetFactory
 
newConcurrentHashMap() - Static method in class edu.stanford.nlp.util.Generics
 
newConcurrentHashMap(int) - Static method in class edu.stanford.nlp.util.Generics
 
newConcurrentHashMap(int, float, int) - Static method in class edu.stanford.nlp.util.Generics
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.ArrayListFactory
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.HashSetFactory
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.LinkedListFactory
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.SizedArrayListFactory
 
newEmptyCollection() - Method in class edu.stanford.nlp.util.CollectionFactory.TreeSetFactory
 
newgeneThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
newGrad - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
newHashMap() - Static method in class edu.stanford.nlp.util.Generics
 
newHashMap(int) - Static method in class edu.stanford.nlp.util.Generics
 
newHashMap(Map<? extends K, ? extends V>) - Static method in class edu.stanford.nlp.util.Generics
 
newHashSet() - Static method in class edu.stanford.nlp.util.Generics
 
newHashSet(int) - Static method in class edu.stanford.nlp.util.Generics
 
newHashSet(Collection<? extends E>) - Static method in class edu.stanford.nlp.util.Generics
 
newIndex() - Static method in class edu.stanford.nlp.util.Generics
 
newInterner() - Static method in class edu.stanford.nlp.util.Generics
 
newLabel(String) - Method in interface edu.stanford.nlp.ling.LabelFactory
Make a new label with this String as the value.
newLabel(String, int) - Method in interface edu.stanford.nlp.ling.LabelFactory
Make a new label with this String as the value, and the type determined in an implementation-dependent way from the options value.
newLabel(Label) - Method in interface edu.stanford.nlp.ling.LabelFactory
Create a new Label, where the label is formed from the Label object passed in.
newLabel(String) - Method in class edu.stanford.nlp.ling.StringLabelFactory
Make a new label with this String as the "name".
newLabel(String, int) - Method in class edu.stanford.nlp.ling.StringLabelFactory
Make a new label with this String as the "name".
newLabel(Label) - Method in class edu.stanford.nlp.ling.StringLabelFactory
Create a new StringLabel, where the label is formed from the Label object passed in.
newLabel(String) - Method in class edu.stanford.nlp.ling.TaggedWordFactory
Make a new label with this String as the value (word).
newLabel(String, int) - Method in class edu.stanford.nlp.ling.TaggedWordFactory
Make a new label with this String as a value component.
newLabel(Label) - Method in class edu.stanford.nlp.ling.TaggedWordFactory
Create a new TaggedWord Label, where the label is formed from the Label object passed in.
newLabel(String) - Method in class edu.stanford.nlp.ling.WordFactory
Create a new word, where the label is formed from the String passed in.
newLabel(String, int) - Method in class edu.stanford.nlp.ling.WordFactory
Create a new word, where the label is formed from the String passed in.
newLabel(Label) - Method in class edu.stanford.nlp.ling.WordFactory
Create a new Word Label, where the label is formed from the Label object passed in.
newLabel(String) - Method in class edu.stanford.nlp.ling.WordLemmaTagFactory
Make a new label with this String as the value (word).
newLabel(String, int) - Method in class edu.stanford.nlp.ling.WordLemmaTagFactory
Make a new label with this String as a value component.
newLabel(Label) - Method in class edu.stanford.nlp.ling.WordLemmaTagFactory
Create a new WordLemmaTag Label, where the label is formed from the Label object passed in.
newLabel(String) - Method in class edu.stanford.nlp.ling.WordTagFactory
Make a new label with this String as the value (word).
newLabel(String, int) - Method in class edu.stanford.nlp.ling.WordTagFactory
Make a new label with this String as a value component.
newLabel(Label) - Method in class edu.stanford.nlp.ling.WordTagFactory
Create a new WordTag Label, where the label is formed from the Label object passed in.
newLabelFromString(String) - Method in interface edu.stanford.nlp.ling.LabelFactory
Make a new label.
newLabelFromString(String) - Method in class edu.stanford.nlp.ling.StringLabelFactory
Make a new label with this String as the "name".
newLabelFromString(String) - Method in class edu.stanford.nlp.ling.TaggedWordFactory
Create a new word, where the label is formed from the String passed in.
newLabelFromString(String) - Method in class edu.stanford.nlp.ling.WordFactory
Create a new word, where the label is formed from the String passed in.
newLabelFromString(String) - Method in class edu.stanford.nlp.ling.WordLemmaTagFactory
Create a new word, where the label is formed from the String passed in.
newLabelFromString(String) - Method in class edu.stanford.nlp.ling.WordTagFactory
Create a new word, where the label is formed from the String passed in.
newLinkedList() - Static method in class edu.stanford.nlp.util.Generics
 
newLinkedList(Collection<? extends E>) - Static method in class edu.stanford.nlp.util.Generics
 
newMap() - Method in class edu.stanford.nlp.util.MapFactory
Returns a new non-parameterized map of a particular sort.
newMap(int) - Method in class edu.stanford.nlp.util.MapFactory
Returns a new non-parameterized map of a particular sort with an initial capacity.
newPair(T1, T2) - Static method in class edu.stanford.nlp.util.Generics
 
newStack() - Static method in class edu.stanford.nlp.util.Generics
 
newSynchronizedInterner(Interner<T>) - Static method in class edu.stanford.nlp.util.Generics
 
newSynchronizedInterner(Interner<T>, Object) - Static method in class edu.stanford.nlp.util.Generics
 
newTreeMap() - Static method in class edu.stanford.nlp.util.Generics
 
newTreeSet() - Static method in class edu.stanford.nlp.util.Generics
 
newTreeSet(Comparator<? super E>) - Static method in class edu.stanford.nlp.util.Generics
 
newTreeSet(SortedSet<E>) - Static method in class edu.stanford.nlp.util.Generics
 
newTriple(T1, T2, T3) - Static method in class edu.stanford.nlp.util.Generics
 
newWeakHashMap() - Static method in class edu.stanford.nlp.util.Generics
 
newWeakReference(T) - Static method in class edu.stanford.nlp.util.Generics
 
newX - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
next() - Method in class edu.stanford.nlp.objectbank.LineIterator
 
next() - Method in class edu.stanford.nlp.process.Morphology
 
next() - Method in class edu.stanford.nlp.util.AbstractIterator
 
next() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
next() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns the element in the queue with highest priority, and pops it from the queue.
NO_PRIOR - Static variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
noMidNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
NominalDataReader - Class in edu.stanford.nlp.classify
 
NominalDataReader() - Constructor for class edu.stanford.nlp.classify.NominalDataReader
 
noop(Object) - Static method in class edu.stanford.nlp.util.ErasureUtils
Does nothing, occasionally used to make Java happy that a value is used
norm(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes 2-norm of vector
norm(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes 2-norm of vector
norm_1(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes 1-norm of vector
norm_1(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes 1-norm of vector
norm_inf(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes inf-norm of vector
norm_inf(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes inf-norm of vector
normalizationTable - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
normalize(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Makes the values in this array sum to 1.0.
normalize(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Makes the values in this array sum to 1.0.
normalize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
normalize(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Normalizes the target counter in-place, so the sum of the resulting values equals 1.
normalizeTerms - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
normalizeTimex - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
normTableEncoding - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
NOWORDSHAPE - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
nthIndex(String, char, int) - Static method in class edu.stanford.nlp.util.StringUtils
Returns the index of the nth occurrence of ch in s, or -1 if there are less than n occurrences of ch.
numBatches - Variable in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
numBatches - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
numberEquivalenceDistSim - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
If this is set to true, all digit characters get mapped to '9' in a distsim lexicon and for lookup.
numClasses - Variable in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
numClasses() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
numClasses - Variable in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
numClasses - Variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
numClasses - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
numCorrect(int) - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
how many correct do we have if we return the most confident num recall ones
numDatasetsPerFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numFeatures - Variable in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
numFeatures() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
numFeatures - Variable in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
numFeatures - Variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
numFeatures - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
numFeatureTokens() - Method in class edu.stanford.nlp.classify.GeneralDataset
returns the number of feature tokens in the Dataset.
numFeatureTypes() - Method in class edu.stanford.nlp.classify.GeneralDataset
returns the number of distinct feature types in the Dataset.
numFolds - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numPasses - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
numPasses - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
numRows(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
numRuns - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numSamples - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numSamples() - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
numStartLayers - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numTimesPruneFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numTimesRemoveTopN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
numToForcePrint() - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ApproximateRepeatSemantics
 
numToForcePrint() - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ExactRepeatSemantics
 
numToForcePrint() - Method in interface edu.stanford.nlp.util.logging.RepeatedRecordHandler.RepeatSemantics
 
numValues - Variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 

O

object() - Method in class edu.stanford.nlp.util.ScoredObject
 
ObjectBank<E> - Class in edu.stanford.nlp.objectbank
The ObjectBank class is designed to make it easy to change the format/source of data read in by other classes and to standardize how data is read in javaNLP classes.
ObjectBank(ReaderIteratorFactory, IteratorFromReaderFactory<E>) - Constructor for class edu.stanford.nlp.objectbank.ObjectBank
This creates a new ObjectBank with the given ReaderIteratorFactory and ObjectIteratorFactory.
ObjectBank.PathToFileFunction - Class in edu.stanford.nlp.objectbank
This is handy for having getLineIterator return a collection of files for feeding into another ObjectBank.
ObjectBank.PathToFileFunction() - Constructor for class edu.stanford.nlp.objectbank.ObjectBank.PathToFileFunction
 
objects(int[]) - Method in class edu.stanford.nlp.util.HashIndex
Looks up the objects corresponding to an array of indices, and returns them in a Collection.
objects(int[]) - Method in interface edu.stanford.nlp.util.Index
Looks up the objects corresponding to an array of indices, and returns them in a Collection.
objectsList() - Method in class edu.stanford.nlp.util.HashIndex
Returns a complete List of indexed objects, in the order of their indices.
objectsList() - Method in interface edu.stanford.nlp.util.Index
Returns a complete List of indexed objects, in the order of their indices.
objectToColumnString(Object, String, String[]) - Static method in class edu.stanford.nlp.util.StringUtils
Converts an object into a tab delimited string with given fields Requires the object has public access for the specified fields
ocrFold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ocrTrain - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
OFFSET_COMPARATOR - Static variable in interface edu.stanford.nlp.util.HasInterval
 
oldKey - Variable in enum edu.stanford.nlp.ling.AnnotationLookup.KeyLookup
 
oneTailedFishersExact(int, int, int, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Find a one-tailed Fisher's exact probability.
openFile(File) - Static method in class edu.stanford.nlp.io.IOUtils
Quietly opens a File.
opFmeasure() - Method in class edu.stanford.nlp.classify.PRCurve
 
optFmeasure(int) - Method in class edu.stanford.nlp.classify.PRCurve
what is the optimal f-measure we can achieve given recall guesses using the optimal monotonic function
optimalAccuracy() - Method in class edu.stanford.nlp.classify.PRCurve
 
optimalCwa() - Method in class edu.stanford.nlp.classify.PRCurve
optimal confidence weighted accuracy assuming for each recall we can fit an optimal monotonic function
optimalCwaArray() - Method in class edu.stanford.nlp.classify.PRCurve
confidence weighted accuracy assuming the scores are probabilities and using .5 as treshold
optimizedDotProduct(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
This method does not check entries for NAN or INFINITY values in the doubles returned.
originalText() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the String which is the original character sequence of the token.
originalText() - Method in interface edu.stanford.nlp.ling.HasContext
Return the String which is the original character sequence of the token.
out() - Static method in class edu.stanford.nlp.util.logging.Redwood.ConsoleHandler
 
outDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
outputEncoding - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
outputFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
outputFormat - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
outputFrequency - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
OutputHandler - Class in edu.stanford.nlp.util.logging
An abstract handler incorporating the logic of outputing a log message, to some source.
OutputHandler() - Constructor for class edu.stanford.nlp.util.logging.OutputHandler
 
outputIterationsToFile - Variable in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
outputIterationsToFile - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
outputIterationsToFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
outputToFile - Variable in class edu.stanford.nlp.optimization.QNMinimizer
 
overlaps(Interval<E>) - Method in class edu.stanford.nlp.util.Interval
Check whether this interval overlaps with the other interval (i.e.

P

pad - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
pad(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
Return a String of length a minimum of totalChars characters by padding the input String str at the right end with spaces.
pad(Object, int) - Static method in class edu.stanford.nlp.util.StringUtils
Pads the toString value of the given Object.
padLeft(String, int, char) - Static method in class edu.stanford.nlp.util.StringUtils
Pads the given String to the left with the given character to ensure that it's at least totalChars long.
padLeft(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
Pads the given String to the left with spaces to ensure that it's at least totalChars long.
padLeft(Object, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
padLeft(int, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
padLeft(double, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
padLeftOrTrim(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
Pad or trim so as to produce a string of exactly a certain length.
padOrTrim(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
Pad or trim so as to produce a string of exactly a certain length.
padOrTrim(Object, int) - Static method in class edu.stanford.nlp.util.StringUtils
Pad or trim the toString value of the given Object.
Pair<T1,T2> - Class in edu.stanford.nlp.util
Pair is a Class for holding mutable pairs of objects.
Pair() - Constructor for class edu.stanford.nlp.util.Pair
 
Pair(T1, T2) - Constructor for class edu.stanford.nlp.util.Pair
 
pairwiseAdd(int[], int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseAdd(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseAdd(float[], float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseAddInPlace(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseAddInPlace(double[], int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseAddInPlace(double[], short[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseMultiply(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Assumes that both arrays have same length.
pairwiseMultiply(float[], float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Assumes that both arrays have same length.
pairwiseMultiply(double[], double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Puts the result in the result array.
pairwiseMultiply(float[], float[], float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Puts the result in the result array.
pairwiseScaleAdd(double[], double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseScaleAddInPlace(double[], double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseSubtract(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseSubtract(float[], float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
pairwiseSubtractInPlace(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
parse(Properties) - Static method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Configure Redwood (from scratch) based on a Properties file.
parseCommandLineArguments(String[]) - Static method in class edu.stanford.nlp.util.StringUtils
A simpler form of command line argument parsing.
parseCommandLineArguments(String[], boolean) - Static method in class edu.stanford.nlp.util.StringUtils
A simpler form of command line argument parsing.
parseMethod(String) - Static method in enum edu.stanford.nlp.optimization.StochasticCalculateMethods
 
partitionIntoFolds(List<T>, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Split a list into numFolds (roughly) equally sized folds.
pearsonCorrelation(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Direct computation of Pearson product-moment correlation coefficient.
peek() - Method in class edu.stanford.nlp.objectbank.LineIterator
 
pennPOSToWordnetPOS(String) - Static method in class edu.stanford.nlp.util.StringUtils
Computes the WordNet 2.0 POS tag corresponding to the PTB POS tag s.
perturbCounts(C, Random, double) - Static method in class edu.stanford.nlp.stats.Counters
 
phraseGazettes - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
plus(DoubleAD, DoubleAD) - Static method in class edu.stanford.nlp.math.ADMath
 
plusConst(DoubleAD, double) - Static method in class edu.stanford.nlp.math.ADMath
 
plusEquals(DoubleAD) - Method in class edu.stanford.nlp.math.DoubleAD
 
plusEqualsConst(double) - Method in class edu.stanford.nlp.math.DoubleAD
 
pointwiseMutualInformation(Counter<T1>, Counter<T2>, Counter<Pair<T1, T2>>, Pair<T1, T2>) - Static method in class edu.stanford.nlp.stats.Counters
 
poisson(int, double) - Static method in class edu.stanford.nlp.math.SloppyMath
 
pow(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
raises each entry in array a by power c
pow(float[], float) - Static method in class edu.stanford.nlp.math.ArrayMath
raises each entry in array a by power c
pow(double, double) - Static method in class edu.stanford.nlp.math.SloppyMath
Returns an approximation to Math.pow(a,b) that is ~27x faster with a margin of error possibly around ~10%.
pow(Counter<T>, double) - Static method in class edu.stanford.nlp.stats.Counters
 
powerSet(Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns the powerset (the set of all subsets) of set s.
powInPlace(double[], double) - Static method in class edu.stanford.nlp.math.ArrayMath
Scales the values in this array by c.
powInPlace(float[], float) - Static method in class edu.stanford.nlp.math.ArrayMath
Sets the values in this array by to their value taken to cth power.
powInPlace(Counter<T>, double) - Static method in class edu.stanford.nlp.stats.Counters
 
powNormalized(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns a counter where each element corresponds to the normalized count of the corresponding element in c raised to the given power.
PRCurve - Class in edu.stanford.nlp.classify
 
PRCurve(String) - Constructor for class edu.stanford.nlp.classify.PRCurve
reads scores with classes from a file, sorts by score and creates the arrays
PRCurve(String, boolean) - Constructor for class edu.stanford.nlp.classify.PRCurve
reads scores with classes from a file, sorts by score and creates the arrays
PRCurve(List<Pair<Double, Integer>>) - Constructor for class edu.stanford.nlp.classify.PRCurve
 
precision(int) - Method in class edu.stanford.nlp.classify.PRCurve
what is the best precision at the given recall
predProp - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
prettyLog(Redwood.RedwoodChannels, String) - Method in class edu.stanford.nlp.stats.ClassicCounter
Pretty logs the current object to specific Redwood channels.
prettyLog(Redwood.RedwoodChannels, String) - Method in class edu.stanford.nlp.stats.IntCounter
Pretty logs the current object to specific Redwood channels.
prettyLog(Redwood.RedwoodChannels, String) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Pretty logs the current object to specific Redwood channels.
prettyLog(Redwood.RedwoodChannels, String) - Method in interface edu.stanford.nlp.util.logging.PrettyLoggable
Pretty logs the current object to specific Redwood channels.
prettyLog(Object) - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
PrettyLog an object using these channels.
prettyLog(String, Object) - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
PrettyLog an object with a description using these channels.
prettyLog(Object) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
prettyLog(String, Object) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
prettyLog(Redwood.RedwoodChannels, String) - Method in class edu.stanford.nlp.util.Pair
Pretty logs the current object to specific Redwood channels.
prettyLog(Redwood.RedwoodChannels, String) - Method in class edu.stanford.nlp.util.Triple
Pretty logs the current object to specific Redwood channels.
PrettyLoggable - Interface in edu.stanford.nlp.util.logging
Indicates that a class supports "pretty logging".
PrettyLogger - Class in edu.stanford.nlp.util.logging
Primarily for debugging, PrettyLogger helps you dump various collection objects in a reasonably structured way via Redwood logging.
print(PrintStream) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
print() - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
print() - Method in class edu.stanford.nlp.util.IntTuple
 
print(String) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Print a string to an output without the trailing newline.
print(String) - Method in class edu.stanford.nlp.util.logging.Redwood.ConsoleHandler
Print a string to the console, in STDOUT, without the trailing newline
print(String) - Method in class edu.stanford.nlp.util.logging.Redwood.FileHandler
Print a string to an output without the trailing newline.
print(boolean) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(char) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(int) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(long) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(float) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(double) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(char[]) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(String) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
print(Object) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
printChannels(int) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
Print (to console) a margin with the channels of a given log message.
printChannels() - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
Print (to console) a margin with the channels of a given log message.
printChannels(int) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Print channels to the left of log messages
printClassifier - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printClassifierParam - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printCounterComparison(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Great for debugging.
printCounterComparison(Counter<E>, Counter<E>, PrintStream) - Static method in class edu.stanford.nlp.stats.Counters
Great for debugging.
printCounterComparison(Counter<E>, Counter<E>, PrintWriter) - Static method in class edu.stanford.nlp.stats.Counters
Prints one or more lines (with a newline at the end) describing the difference between the two Counters.
printCounterSortedByKeys(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
printErrInvocationString(String, String[]) - Static method in class edu.stanford.nlp.util.StringUtils
 
printf(String, Object...) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
printf(Locale, String, Object...) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
printFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printFeaturesUpto - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printFirstOrderProbs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printFullFeatureMatrix(PrintWriter) - Method in class edu.stanford.nlp.classify.Dataset
prints the full feature matrix in tab-delimited form.
printFullFeatureMatrix(PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
prints the full feature matrix in tab-delimited form.
printFullFeatureMatrixWithValues(PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
Modification of printFullFeatureMatrix to correct bugs & print values (Rajat).
printGazFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printLabelValue - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
println(Object) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
println(boolean) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(char) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(int) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(long) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(float) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(double) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(char[]) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(String) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println(Object) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
println() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
printMinMax - Variable in class edu.stanford.nlp.optimization.SMDMinimizer
 
printNR - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printProbs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
printSparseFeatureMatrix() - Method in class edu.stanford.nlp.classify.Dataset
prints the sparse feature matrix using Dataset.printSparseFeatureMatrix() to System.out.
printSparseFeatureMatrix(PrintWriter) - Method in class edu.stanford.nlp.classify.Dataset
prints a sparse feature matrix representation of the Dataset.
printSparseFeatureMatrix() - Method in class edu.stanford.nlp.classify.RVFDataset
Prints the sparse feature matrix using RVFDataset.printSparseFeatureMatrix(PrintWriter) to System.out.
printSparseFeatureMatrix(PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
Prints a sparse feature matrix representation of the Dataset.
printSparseFeatureValues(PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
Prints a sparse feature-value output of the Dataset.
printSparseFeatureValues(int, PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
Prints a sparse feature-value output of the Dataset.
printStringOneCharPerLine(String) - Static method in class edu.stanford.nlp.util.StringUtils
 
printSVMLightFormat(PrintWriter, ClassicCounter<Integer>, int) - Static method in class edu.stanford.nlp.classify.Dataset
Need to sort the counter by feature keys and dump it
printSVMLightFormat() - Method in class edu.stanford.nlp.classify.GeneralDataset
Dumps the Dataset as a training/test file for SVMLight.
printSVMLightFormat(PrintWriter) - Method in class edu.stanford.nlp.classify.GeneralDataset
Print SVM Light Format file.
printToFile(File, String, boolean, boolean, String) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFile(File, String, boolean) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFile(File, String) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFile(String, String, boolean) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFile(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFileLn(File, String, boolean) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printToFileLn(String, String, boolean) - Static method in class edu.stanford.nlp.util.StringUtils
Prints to a file.
printXML - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
prior - Variable in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
prior - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
priorDerivative - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
PriorityQueue<E> - Interface in edu.stanford.nlp.util
A Set that also represents an ordering of its elements, and responds quickly to add(), changePriority(), removeFirst(), and getFirst() method calls.
priors(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
priorType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ProbabilisticClassifier<L,F> - Interface in edu.stanford.nlp.classify
 
ProbabilisticClassifierCreator<L,F> - Interface in edu.stanford.nlp.classify
Creates a probablic classifier with given weights
ProbabilityDistribution<E> - Interface in edu.stanford.nlp.stats
This is an interface for probability measures, which will allow samples to be drawn and the probability of objects computed.
probabilityOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns a counter mapping from each class name to the probability of that class for a certain example.
probabilityOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
probabilityOf(int[]) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
probabilityOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
probabilityOf(Collection<F>, L) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
probabilityOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
probabilityOf(Counter<F>, L) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
probabilityOf(Datum<L, F>) - Method in interface edu.stanford.nlp.classify.ProbabilisticClassifier
 
probabilityOf(E) - Method in class edu.stanford.nlp.stats.Distribution
Returns the normalized count of the given object.
probabilityOf(E) - Method in interface edu.stanford.nlp.stats.ProbabilityDistribution
 
probs - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
product(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the product of c1 and c2.
propFileToProperties(String) - Static method in class edu.stanford.nlp.util.StringUtils
This method reads in properties listed in a file in the format prop=value, one property per line.
props - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
purgeDatasets - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
purgeFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
pushDir - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
put(K, V) - Method in class edu.stanford.nlp.util.ArrayMap
 

Q

QNMinimizer - Class in edu.stanford.nlp.optimization
An implementation of L-BFGS for Quasi Newton unconstrained minimization.
QNMinimizer(int) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer(int, boolean) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer() - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer(Function) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer(FloatFunction) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer(Function, int) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer(Function, int, boolean) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer
 
QNMinimizer.eLineSearch - Enum in edu.stanford.nlp.optimization
 
QNMinimizer.eScaling - Enum in edu.stanford.nlp.optimization
 
QNMinimizer.eState - Enum in edu.stanford.nlp.optimization
 
QNMinimizer.QNInfo - Class in edu.stanford.nlp.optimization
The QNInfo class is used to store information about the Quasi Newton update.
QNMinimizer.QNInfo(int) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
QNMinimizer.QNInfo() - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
QNMinimizer.QNInfo(List<double[]>, List<double[]>) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
QNMinimizer.Record - Class in edu.stanford.nlp.optimization
The Record class is used to collect information about the function value over a series of iterations.
QNMinimizer.Record() - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(PrintWriter) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(boolean) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(boolean, Function) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(boolean, Function, double) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(boolean, Function, double, PrintWriter) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.Record(boolean, Function, double, double) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.Record
 
QNMinimizer.SurpriseConvergence - Class in edu.stanford.nlp.optimization
 
QNMinimizer.SurpriseConvergence(String) - Constructor for class edu.stanford.nlp.optimization.QNMinimizer.SurpriseConvergence
 
QNPasses - Variable in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
QNPasses - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
QNsize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
QNsize2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
QUADRATIC_PRIOR - Static variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
QUARTIC_PRIOR - Static variable in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
queuedTracks - Variable in class edu.stanford.nlp.util.logging.OutputHandler
A list of tracks which have been started but not yet printed as no log messages are in them yet.
quiet - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
quiet - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 

R

randGenerator - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
randomize(int) - Method in class edu.stanford.nlp.classify.GeneralDataset
Randomizes the data array in place Note: this cannot change the values array or the datum weights, so redefine this for RVFDataset and WeightedDataset!
randomize(int) - Method in class edu.stanford.nlp.classify.RVFDataset
Randomizes the data array in place Needs to be redefined here because we need to randomize the values as well
randomize(int) - Method in class edu.stanford.nlp.classify.WeightedDataset
Randomizes the data array in place Needs to be redefined here because we need to randomize the weights as well
randomizedRatio - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
read(DataInputStream) - Method in class edu.stanford.nlp.ling.WordTag
 
readClassifier(String) - Static method in class edu.stanford.nlp.classify.LinearClassifier
Loads a classifier from a file.
readColumnSet(String, int) - Static method in class edu.stanford.nlp.io.IOUtils
Read column as set
readCSVStrictly(char[], int) - Static method in class edu.stanford.nlp.io.IOUtils
Read a CSV file character by character.
readCSVStrictly(String, int) - Static method in class edu.stanford.nlp.io.IOUtils
 
readCSVWithHeader(String, char, char) - Static method in class edu.stanford.nlp.io.IOUtils
Read in a CSV formatted file with a header row
readCSVWithHeader(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
readerAndWriter - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ReaderIteratorFactory - Class in edu.stanford.nlp.objectbank
A ReaderIteratorFactory provides a means of getting an Iterator which returns java.util.Readers over a Collection of input sources.
ReaderIteratorFactory(Collection<?>) - Constructor for class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Constructs a ReaderIteratorFactory from the input sources contained in the Collection.
ReaderIteratorFactory(Collection<?>, String) - Constructor for class edu.stanford.nlp.objectbank.ReaderIteratorFactory
 
ReaderIteratorFactory(Object) - Constructor for class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Convenience constructor to construct a ReaderIteratorFactory from a single input source.
ReaderIteratorFactory(Object, String) - Constructor for class edu.stanford.nlp.objectbank.ReaderIteratorFactory
 
ReaderIteratorFactory() - Constructor for class edu.stanford.nlp.objectbank.ReaderIteratorFactory
 
readLines(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns an Iterable of the lines in the file.
readLines(File) - Static method in class edu.stanford.nlp.io.IOUtils
Returns an Iterable of the lines in the file.
readLines(File, Class<? extends InputStream>) - Static method in class edu.stanford.nlp.io.IOUtils
Returns an Iterable of the lines in the file, wrapping the generated FileInputStream with an instance of the supplied class.
readMap(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
readObjectFromColumns(Class, String, String[], String) - Static method in class edu.stanford.nlp.io.IOUtils
 
readObjectFromFile(File) - Static method in class edu.stanford.nlp.io.IOUtils
Read an object from a stored file.
readObjectFromFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
Read an object from a stored file.
readObjectFromFileNoExceptions(File) - Static method in class edu.stanford.nlp.io.IOUtils
Read an object from a stored file without throwing exceptions.
readObjectFromObjectStream(ObjectInputStream) - Static method in class edu.stanford.nlp.io.IOUtils
 
readReaderFromString(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
readReaderFromString(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
Open a BufferedReader to a file or URL specified by a String name.
readStdin - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
readStreamFromString(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
readStringPair(DataInputStream) - Static method in class edu.stanford.nlp.util.Pair
Read a string representation of a Pair from a DataStream.
readSVMLightFormat(String) - Static method in class edu.stanford.nlp.classify.Dataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String, List<String>) - Static method in class edu.stanford.nlp.classify.Dataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String, Index<String>, Index<String>) - Static method in class edu.stanford.nlp.classify.Dataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String, Index<String>, Index<String>, List<String>) - Static method in class edu.stanford.nlp.classify.Dataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String) - Static method in class edu.stanford.nlp.classify.RVFDataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String, List<String>) - Static method in class edu.stanford.nlp.classify.RVFDataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(String, Index<String>, Index<String>) - Static method in class edu.stanford.nlp.classify.RVFDataset
Constructs a Dataset by reading in a file in SVM light format.
readSVMLightFormat(File) - Method in class edu.stanford.nlp.classify.RVFDataset
Read SVM-light formatted data into this dataset.
readTestExamples(String) - Method in class edu.stanford.nlp.classify.ColumnDataClassifier
Read a data set from a file at test time, and return it.
readTrainingExamples(String) - Method in class edu.stanford.nlp.classify.ColumnDataClassifier
Read a set of training examples from a file, and return the data in a featurized form.
recalculatePrevBatch - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
RED - Static variable in class edu.stanford.nlp.classify.ClassifierExample
 
RED - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
Redwood - Class in edu.stanford.nlp.util.logging
A hierarchical channel based logger.
Redwood() - Constructor for class edu.stanford.nlp.util.logging.Redwood
 
Redwood.ConsoleHandler - Class in edu.stanford.nlp.util.logging
Default output handler which actually prints things to the real System.out
Redwood.FileHandler - Class in edu.stanford.nlp.util.logging
Handler which prints to a specified file
Redwood.FileHandler(String) - Constructor for class edu.stanford.nlp.util.logging.Redwood.FileHandler
 
Redwood.Flag - Enum in edu.stanford.nlp.util.logging
Standard channels; enum for the sake of efficiency
Redwood.Record - Class in edu.stanford.nlp.util.logging
A log record, which encapsulates the information needed to eventually display the enclosed message.
Redwood.Record(Object, Object[], int, StackTraceElement, long) - Constructor for class edu.stanford.nlp.util.logging.Redwood.Record
Create a new Record, based on the content of the log, the channels, and the depth
Redwood.Record(Object, Object[], int, String, String, long) - Constructor for class edu.stanford.nlp.util.logging.Redwood.Record
Create a new Record, based on the content of the log, the channels, and the depth
Redwood.RecordHandlerTree - Class in edu.stanford.nlp.util.logging
A tree structure of record handlers
Redwood.RecordHandlerTree() - Constructor for class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
Redwood.RecordHandlerTree(LogRecordHandler) - Constructor for class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
Redwood.RedwoodChannels - Class in edu.stanford.nlp.util.logging
Represents a collection of channels.
Redwood.RedwoodChannels(Object...) - Constructor for class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
 
Redwood.Util - Class in edu.stanford.nlp.util.logging
A utility class for Redwood intended for static import (import static edu.stanford.nlp.util.logging.Redwood.Util.*;), providing a wrapper for Redwood functions and adding utility shortcuts
Redwood.Util() - Constructor for class edu.stanford.nlp.util.logging.Redwood.Util
 
RedwoodConfiguration - Class in edu.stanford.nlp.util.logging
A class which encapsulates configuration settings for Redwood.
RedwoodConfiguration() - Constructor for class edu.stanford.nlp.util.logging.RedwoodConfiguration
Private constructor to prevent use of "new RedwoodConfiguration()"
RedwoodPrintStream - Class in edu.stanford.nlp.util.logging
A PrintStream that writes to Redwood logs.
RedwoodPrintStream(Redwood.Flag, PrintStream) - Constructor for class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
ReflectionLoading - Class in edu.stanford.nlp.util
The goal of this class is to make it easier to load stuff by reflection.
ReflectionLoading.ReflectionLoadingException - Exception in edu.stanford.nlp.util
This class encapsulates all of the exceptions that can be thrown when loading something by reflection.
ReflectionLoading.ReflectionLoadingException(Throwable) - Constructor for exception edu.stanford.nlp.util.ReflectionLoading.ReflectionLoadingException
 
regexesToPatterns(Iterable<String>) - Static method in class edu.stanford.nlp.util.StringUtils
 
regexGroups(Pattern, String) - Static method in class edu.stanford.nlp.util.StringUtils
Given a pattern and a string, returns a list with the values of the captured groups in the pattern.
REL_FLAGS_AFTER - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_EE_AFTER - Static variable in class edu.stanford.nlp.util.Interval
The first interval ends after the second ends
REL_FLAGS_EE_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
The first interval ends before the second ends
REL_FLAGS_EE_SAME - Static variable in class edu.stanford.nlp.util.Interval
Both intervals have the same end point
REL_FLAGS_EE_SHIFT - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_EE_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
The relationship between the end points of the two intervals is unknown (used for fuzzy intervals)
REL_FLAGS_ES_AFTER - Static variable in class edu.stanford.nlp.util.Interval
The end point of the first interval is after the start point of the second interval (the two intervals overlap)
REL_FLAGS_ES_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
The end point of the first interval is before the start point of the second interval (the first interval is before the second)
REL_FLAGS_ES_SAME - Static variable in class edu.stanford.nlp.util.Interval
The end point of the first interval is the same as the start point of the second interval (the first interval is before the second)
REL_FLAGS_ES_SHIFT - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_ES_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
The relationship between the end point of the first interval and the start point of the second interval is unknown (used for fuzzy intervals)
REL_FLAGS_INTERVAL_AFTER - Static variable in class edu.stanford.nlp.util.Interval
The first interval is entirely after the second interval (the start of the first interval happens after the end of the second)
REL_FLAGS_INTERVAL_ALMOST_AFTER - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_INTERVAL_ALMOST_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_INTERVAL_ALMOST_SAME - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_INTERVAL_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
The first interval is entirely before the second interval (the end of the first interval happens before the start of the second)
REL_FLAGS_INTERVAL_CONTAIN - Static variable in class edu.stanford.nlp.util.Interval
The first interval contains the second interval.
REL_FLAGS_INTERVAL_FUZZY - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_INTERVAL_INSIDE - Static variable in class edu.stanford.nlp.util.Interval
The first interval is inside the second interval.
REL_FLAGS_INTERVAL_OVERLAP - Static variable in class edu.stanford.nlp.util.Interval
The first interval overlaps with the second interval.
REL_FLAGS_INTERVAL_SAME - Static variable in class edu.stanford.nlp.util.Interval
The intervals are the same (have the same start and end points).
REL_FLAGS_INTERVAL_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
It is uncertain what the relationship between the two intervals are...
REL_FLAGS_SAME - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_SE_AFTER - Static variable in class edu.stanford.nlp.util.Interval
The start point of the first interval is after the end point of the second interval (the second interval is before the first)
REL_FLAGS_SE_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
The start point of the first interval is before the end point of the second interval (the two intervals overlap)
REL_FLAGS_SE_SAME - Static variable in class edu.stanford.nlp.util.Interval
The start point of the first interval is the same as the end point of the second interval (the second interval is before the first)
REL_FLAGS_SE_SHIFT - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_SE_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
The relationship between the start point of the first interval and the end point of the second interval is unknown (used for fuzzy intervals)
REL_FLAGS_SS_AFTER - Static variable in class edu.stanford.nlp.util.Interval
The first interval starts after the second starts
REL_FLAGS_SS_BEFORE - Static variable in class edu.stanford.nlp.util.Interval
The first interval starts before the second starts
REL_FLAGS_SS_SAME - Static variable in class edu.stanford.nlp.util.Interval
Both intervals have the same start point
REL_FLAGS_SS_SHIFT - Static variable in class edu.stanford.nlp.util.Interval
 
REL_FLAGS_SS_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
The relationship between the start points of the two intervals is unknown (used for fuzzy intervals)
REL_FLAGS_UNKNOWN - Static variable in class edu.stanford.nlp.util.Interval
 
relaxPriority(E, double) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Promotes a key in the queue, adding it if it wasn't there already.
relaxPriority(E, double) - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Not supported in this implementation.
relaxPriority(E, double) - Method in interface edu.stanford.nlp.util.PriorityQueue
Increases the priority of the E key to the new priority if the old priority was lower than the new priority.
remove(Object) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Unsupported Operation.
remove(Object) - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Removes an Object from the underlying Collection of input sources.
remove(E) - Method in class edu.stanford.nlp.stats.ClassicCounter
Removes the given key and its associated value from this Counter.
remove(E) - Method in interface edu.stanford.nlp.stats.Counter
Removes the given key and its associated value from this Counter.
remove(E) - Method in class edu.stanford.nlp.stats.IntCounter
Removes the given key from this Counter.
remove(K1, K2) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
remove(K1) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
remove(K1, K2) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
remove(K1) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
remove() - Method in class edu.stanford.nlp.util.AbstractIterator
Throws an UnupportedOperationException.
remove(Class<KEY>) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Removes the given key from the map, returning the value removed.
remove(Object) - Method in class edu.stanford.nlp.util.ArrayMap
 
remove() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
remove(Object) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
remove() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Not supported -- next() already removes the head of the queue.
remove(Object) - Method in class edu.stanford.nlp.util.HashIndex
 
remove(Class<KEY>) - Method in interface edu.stanford.nlp.util.TypesafeMap
Removes the given key from the map, returning the value removed.
removeAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Unsupported Operation.
removeAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Removes all Objects in Collection c from the underlying Collection of input sources.
removeAll(Collection<E>) - Method in class edu.stanford.nlp.stats.ClassicCounter
Removes all the given keys from this Counter.
removeAll(Collection<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Removes all the given keys from this Counter.
removeAll(Collection<?>) - Method in class edu.stanford.nlp.util.HashIndex
 
removeAt(double[], int) - Static method in class edu.stanford.nlp.util.ArrayUtils
Removes the element at the specified index from the array, and returns a new array containing the remaining elements.
removeAt(Object[], int) - Static method in class edu.stanford.nlp.util.ArrayUtils
Removes the element at the specified index from the array, and returns a new array containing the remaining elements.
removeBackgroundSingletonFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
removeChild(LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
removeFirst() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Finds the object with the highest priority, removes it, and returns it.
removeFirst() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns the highest-priority element and removes it from the queue.
removeFirst() - Method in interface edu.stanford.nlp.util.PriorityQueue
Finds the object with the highest priority, removes it, and returns it.
removeHandler(Class<E>) - Static method in class edu.stanford.nlp.util.logging.Redwood
Remove a handler from the list
removeKeys(Counter<E>, Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with keys in the given collection
removeObject(List<T>, T) - Static method in class edu.stanford.nlp.util.CollectionUtils
Removes the first occurrence in the list of the specified object, using object identity (==) not equality as the criterion for object presence.
removeTopN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
removeTopNPercent - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
removeZeroCounts() - Method in class edu.stanford.nlp.stats.IntCounter
Removes all keys whose count is 0.
removeZeroCounts() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
renameToBackupName(File) - Static method in class edu.stanford.nlp.io.IOUtils
 
repeat(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
repeat(char, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
RepeatedRecordHandler - Class in edu.stanford.nlp.util.logging
Filters repeated messages and replaces them with the number of times they were logged.
RepeatedRecordHandler(RepeatedRecordHandler.RepeatSemantics) - Constructor for class edu.stanford.nlp.util.logging.RepeatedRecordHandler
Create a new repeated log message handler, using the given semantics for what constitutes a repeated record.
RepeatedRecordHandler.ApproximateRepeatSemantics - Class in edu.stanford.nlp.util.logging
Judges two records to be equal if they come from the same place, and begin with the same string, modulo numbers
RepeatedRecordHandler.ApproximateRepeatSemantics() - Constructor for class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ApproximateRepeatSemantics
 
RepeatedRecordHandler.ExactRepeatSemantics - Class in edu.stanford.nlp.util.logging
Judges two records to be equal if they are from the same place, and have the same message
RepeatedRecordHandler.ExactRepeatSemantics() - Constructor for class edu.stanford.nlp.util.logging.RepeatedRecordHandler.ExactRepeatSemantics
 
RepeatedRecordHandler.RepeatSemantics - Interface in edu.stanford.nlp.util.logging
Determines the semantics of what constitutes a repeated record
report() - Method in class edu.stanford.nlp.util.Timing
Return elapsed time (without stopping timer).
report(String, PrintStream) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time (without stopping timer).
report(String) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time to System.err (without stopping timer).
report(String, PrintWriter) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time (without stopping timer).
resetWeight() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
NOTE: Nothing is actually done with this value.
restart() - Method in class edu.stanford.nlp.util.Timing
Restart timer.
restart(String, PrintStream) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time and restart timer.
restart(String) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time to System.err and restart timer.
restart(String, PrintWriter) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time and restart timer.
restoreSystemStreams() - Static method in class edu.stanford.nlp.util.logging.Redwood
Restores System.out and System.err to their original values
restrictedArgMax(Counter<E>, Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
restrictLabels - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
restrictTransitionsTimit - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
retainAbove(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with counts below the given threshold, returning the set of removed entries.
retainAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Unsupported Operation.
retainAll(Collection<?>) - Method in class edu.stanford.nlp.objectbank.ReaderIteratorFactory
Removes all Objects from the underlying Collection of input sources except those in Collection c
retainBelow(Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with counts above the given threshold, returning the set of removed entries.
retainBottom(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries from c except for the bottom num
retainEntitySubclassification - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
retainKeys(Counter<E>, Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with keys that does not match the given set of keys
retainMatchingKeys(Counter<String>, List<Pattern>) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with keys that does not match one of the given patterns
retainNonZeros(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries with 0 count in the counter, returning the set of removed entries.
retainTop(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries from c except for the top num
retainTopKeyComparable(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
Removes all entries from c except for the top num
returnPreviousValues - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
reverse(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
reverseIndexOrder(TwoDimensionalCounter<K1, K2>) - Static method in class edu.stanford.nlp.stats.TwoDimensionalCounter
Produces a new ConditionalCounter.
rif - Variable in class edu.stanford.nlp.objectbank.ObjectBank
 
rootHandler(LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a custom Log Record Handler to the root of the tree
round(double) - Static method in class edu.stanford.nlp.math.SloppyMath
Round a double to the nearest integer, via conventional rules (.5 rounds up, .49 rounds down), and return the result, still as a double.
round(double, int) - Static method in class edu.stanford.nlp.math.SloppyMath
Round a double to the given number of decimal places, rounding to the nearest value via conventional rules (5 rounds up, 49 rounds down).
run() - Method in class edu.stanford.nlp.util.ByteStreamGobbler
 
run() - Method in class edu.stanford.nlp.util.StreamGobbler
 
RuntimeIOException - Exception in edu.stanford.nlp.io
An unchecked version of IOException.
RuntimeIOException() - Constructor for exception edu.stanford.nlp.io.RuntimeIOException
Creates a new exception.
RuntimeIOException(String) - Constructor for exception edu.stanford.nlp.io.RuntimeIOException
Creates a new exception with a message.
RuntimeIOException(Throwable) - Constructor for exception edu.stanford.nlp.io.RuntimeIOException
Creates a new exception with an embedded cause.
RuntimeIOException(String, Throwable) - Constructor for exception edu.stanford.nlp.io.RuntimeIOException
Creates a new exception with a message and an embedded cause.
rvfcalculate(double[]) - Method in class edu.stanford.nlp.classify.AdaptedGaussianPriorObjectiveFunction
 
rvfcalculate(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
Calculate conditional likelihood for datasets with real-valued features.
RVFClassifier<L,F> - Interface in edu.stanford.nlp.classify
A simple interface for classifying and scoring data points with real-valued features.
RVFDataset<L,F> - Class in edu.stanford.nlp.classify
An interfacing class for ClassifierFactory that incrementally builds a more memory-efficient representation of a List of RVFDatum objects for the purposes of training a Classifier with a ClassifierFactory.
RVFDataset() - Constructor for class edu.stanford.nlp.classify.RVFDataset
 
RVFDataset(int, Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.RVFDataset
 
RVFDataset(Index<F>, Index<L>) - Constructor for class edu.stanford.nlp.classify.RVFDataset
 
RVFDataset(int) - Constructor for class edu.stanford.nlp.classify.RVFDataset
 
RVFDataset(Index<L>, int[], Index<F>, int[][], double[][]) - Constructor for class edu.stanford.nlp.classify.RVFDataset
Constructor that fully specifies a Dataset.
RVFDatum<L,F> - Class in edu.stanford.nlp.ling
A basic implementation of the Datum interface that can be constructed with a Collection of features and one more more labels.
RVFDatum(Counter<F>, L) - Constructor for class edu.stanford.nlp.ling.RVFDatum
Constructs a new RVFDatum with the given features and label.
RVFDatum(Datum<L, F>) - Constructor for class edu.stanford.nlp.ling.RVFDatum
Constructs a new RVFDatum taking the data from a Datum.
RVFDatum(Counter<F>) - Constructor for class edu.stanford.nlp.ling.RVFDatum
Constructs a new RVFDatum with the given features and no labels.
RVFDatum() - Constructor for class edu.stanford.nlp.ling.RVFDatum
Constructs a new RVFDatum with no features or labels.

S

safeMax(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the largest value in a vector of doubles.
safeMean(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the mean of a vector of doubles.
safeMin(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the largest value in a vector of doubles.
saferL2Norm(C) - Static method in class edu.stanford.nlp.stats.Counters
For counters with large # of entries, this scales down each entry in the sum, to prevent an extremely large sum from building up and overwhelming the max double.
saferL2Normalize(C) - Static method in class edu.stanford.nlp.stats.Counters
L2 normalize a counter, using the "safer" L2 normalizer.
safeStdev(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the standard deviation of a vector of doubles.
sample(Counter<T>, Random) - Static method in class edu.stanford.nlp.stats.Counters
Does not assumes c is normalized.
sample(Counter<T>) - Static method in class edu.stanford.nlp.stats.Counters
Does not assumes c is normalized.
sample(List<E>, Random) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
sampleDataset(int, double, boolean) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
sampleFrom() - Method in class edu.stanford.nlp.stats.Distribution
Returns an object sampled from the distribution using Math.random().
sampleFrom(Random) - Method in class edu.stanford.nlp.stats.Distribution
Returns an object sampled from the distribution using a self-provided random number generator.
sampleFromDistribution(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Samples from the distribution over values 0 through d.length given by d.
sampleFromDistribution(double[], Random) - Static method in class edu.stanford.nlp.math.ArrayMath
Samples from the distribution over values 0 through d.length given by d.
sampleFromDistribution(float[], Random) - Static method in class edu.stanford.nlp.math.ArrayMath
Samples from the distribution over values 0 through d.length given by d.
sampleMethod - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
Sampler<T> - Interface in edu.stanford.nlp.stats
An interace for drawing samples from the label space of an object.
sampleWithoutReplacement(int[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
Fills the array with sample from 0 to numArgClasses-1 without replacement.
sampleWithoutReplacement(int[], int, Random) - Static method in class edu.stanford.nlp.math.ArrayMath
Fills the array with sample from 0 to numArgClasses-1 without replacement.
sampleWithoutReplacement(Collection<E>, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Samples without replacement from a collection.
sampleWithoutReplacement(Collection<E>, int, Random) - Static method in class edu.stanford.nlp.util.CollectionUtils
Samples without replacement from a collection, using your own Random number generator.
sampleWithReplacement(Collection<E>, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Samples with replacement from a collection
sampleWithReplacement(Collection<E>, int, Random) - Static method in class edu.stanford.nlp.util.CollectionUtils
Samples with replacement from a collection, using your own Random number generator
save(DataOutputStream) - Method in class edu.stanford.nlp.ling.WordTag
 
save(DataOutputStream) - Method in class edu.stanford.nlp.util.Pair
Write a string representation of a Pair to a DataStream.
save2DCounter(TwoDimensionalCounter<T1, T2>, String) - Static method in class edu.stanford.nlp.stats.Counters
 
save2DCounterSorted(TwoDimensionalCounterInterface<T1, T2>, String) - Static method in class edu.stanford.nlp.stats.Counters
 
saveCounter(Counter<E>, OutputStream) - Static method in class edu.stanford.nlp.stats.Counters
Saves a Counter as one key/count pair per line separated by white space to the given OutputStream.
saveCounter(Counter<E>, String) - Static method in class edu.stanford.nlp.stats.Counters
Saves a Counter to a text file.
saveFeatureIndexToDisk - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
saveToFilename(String) - Method in class edu.stanford.nlp.classify.LinearClassifier
Saves this out to a standard text file, instead of as a serialized Java object.
saveToFilename(String) - Method in class edu.stanford.nlp.util.HashIndex
 
saveToFilename(String) - Method in interface edu.stanford.nlp.util.Index
Save the contents of this index into a file.
saveToWriter(Writer) - Method in class edu.stanford.nlp.util.HashIndex
This saves the contents of this index into string form, as part of a larger text-serialization.
saveToWriter(Writer) - Method in interface edu.stanford.nlp.util.Index
Save the contents of this index into string form, as part of a larger text-serialization.
say(String) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
say(String) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
sayln(String) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
sayln(String) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
scale(C, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns a new Counter which is scaled by the given scale factor.
scale(TwoDimensionalCounter<T1, T2>, double) - Static method in class edu.stanford.nlp.stats.Counters
Creates a new TwoDimensionalCounter where all the counts are scaled by d.
scaleDataset(RVFDataset<L, F>) - Method in class edu.stanford.nlp.classify.RVFDataset
Scales the values of each feature in each linearly using the min and max values found in the training set.
scaleDatasetGaussian(RVFDataset<L, F>) - Method in class edu.stanford.nlp.classify.RVFDataset
 
scaleDatum(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.RVFDataset
Scales the values of each feature linearly using the min and max values found in the training set.
scaleDatumGaussian(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.RVFDataset
 
scaledSGDMethod - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
ScaledSGDMinimizer - Class in edu.stanford.nlp.optimization
Stochastic Gradient Descent To Quasi Newton Minimizer An experimental minimizer which takes a stochastic function (one implementing AbstractStochasticCachingDiffFunction) and executes SGD for the first couple passes, During the final iterations a series of approximate hessian vector products are built up...
ScaledSGDMinimizer(SeqClassifierFlags) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
ScaledSGDMinimizer(double, int, int) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
ScaledSGDMinimizer(double, int, int, int) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
ScaledSGDMinimizer(double, int, int, int, boolean) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
ScaledSGDMinimizer(double, int) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
ScaledSGDMinimizer.weight - Class in edu.stanford.nlp.optimization
 
ScaledSGDMinimizer.weight(double[]) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer.weight
 
ScaledSGDMinimizer.weight(double[], double[]) - Constructor for class edu.stanford.nlp.optimization.ScaledSGDMinimizer.weight
 
scaleFeatures() - Method in class edu.stanford.nlp.classify.RVFDataset
Scales feature values linearly such that each feature value lies between 0 and 1.
scaleFeaturesGaussian() - Method in class edu.stanford.nlp.classify.RVFDataset
 
scaleOpt - Variable in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
scaleUp - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
scaleUp(boolean) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
score(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>) - Method in class edu.stanford.nlp.stats.AccuracyStats
 
score(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>) - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
score() - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
score(ProbabilisticClassifier<L, F>, GeneralDataset<L, F>) - Method in interface edu.stanford.nlp.stats.Scorer
 
score() - Method in interface edu.stanford.nlp.util.Scored
 
score() - Method in class edu.stanford.nlp.util.ScoredObject
 
Scored - Interface in edu.stanford.nlp.util
Scored: This is a simple interface that says that an object can answer requests for the score, or goodness of the object.
ScoredComparator - Class in edu.stanford.nlp.util
ScoredComparator allows one to compare Scored things.
ScoredObject<T> - Class in edu.stanford.nlp.util
Wrapper class for holding a scored object
ScoredObject() - Constructor for class edu.stanford.nlp.util.ScoredObject
 
ScoredObject(T, double) - Constructor for class edu.stanford.nlp.util.ScoredObject
 
scoreOf(Datum<L, F>, L) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns of the score of the Datum for the specified label.
scoreOf(RVFDatum<L, F>, L) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
scoreOf(Collection<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
scoreOf(Counter<F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
Scorer<L> - Interface in edu.stanford.nlp.stats
 
scoresOf(Datum<L, F>) - Method in interface edu.stanford.nlp.classify.Classifier
 
scoresOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Construct a counter with keys the labels of the classifier and values the score (unnormalized log probability) of each class.
scoresOf(int[]) - Method in class edu.stanford.nlp.classify.LinearClassifier
Given a datum's features, construct a counter with keys the labels and values the score (unnormalized log probability) for each class.
scoresOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Deprecated. 
scoresOf(Datum<L, F>, Collection<L>) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
scoresOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
returns the scores for both the classes
scoresOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
scoresOf(RVFDatum<L, F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
scoresOf(Datum<L, F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifier
 
scoresOf(RVFDatum<L, F>) - Method in interface edu.stanford.nlp.classify.RVFClassifier
 
searchAndReplace(String, String, String) - Static method in class edu.stanford.nlp.util.StringUtils
 
searchGraphPrefix - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
searchGraphPrune - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
second - Variable in class edu.stanford.nlp.util.Pair
Direct access is deprecated.
second() - Method in class edu.stanford.nlp.util.Pair
 
second - Variable in class edu.stanford.nlp.util.Triple
 
second() - Method in class edu.stanford.nlp.util.Triple
 
secondKeySet() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
secondKeySet() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
selectFeatures(int, double[]) - Method in class edu.stanford.nlp.classify.Dataset
Generic method to select features based on the feature scores vector provided as an argument.
selectFeaturesBinaryInformationGain(int) - Method in class edu.stanford.nlp.classify.Dataset
 
selectFeaturesFromSet(Set<F>) - Method in class edu.stanford.nlp.classify.RVFDataset
Removes all features from the dataset that are not in featureSet.
selfTest - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
selfTrainConfidenceThreshold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
selfTrainFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
selfTrainIterations - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
selfTrainWindowSize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SemiSupervisedLogConditionalObjectiveFunction - Class in edu.stanford.nlp.classify
Maximizes the conditional likelihood with a given prior.
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction, AbstractCachingDiffFunction, LogPrior, double) - Constructor for class edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction
 
SemiSupervisedLogConditionalObjectiveFunction(AbstractCachingDiffFunction, AbstractCachingDiffFunction, LogPrior) - Constructor for class edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction
 
sentIndex() - Method in class edu.stanford.nlp.ling.CoreLabel
sentIndex() - Method in interface edu.stanford.nlp.ling.HasIndex
 
SeqClassifierFlags - Class in edu.stanford.nlp.sequences
Flags for sequence classifiers.
SeqClassifierFlags() - Constructor for class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SeqClassifierFlags(Properties) - Constructor for class edu.stanford.nlp.sequences.SeqClassifierFlags
Create a new SeqClassifierFlags object and initialize it using values in the Properties object.
serializeCounter(Counter<T>, String) - Static method in class edu.stanford.nlp.stats.Counters
 
serializeDatasetsDir - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
serializedDictionary - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
serializeTo - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
serializeToText - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
serializeWeights(String, double[]) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
serializeWeights(String, double[], double[]) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
set(double, double) - Method in class edu.stanford.nlp.math.DoubleAD
 
set(T1) - Method in interface edu.stanford.nlp.optimization.StochasticMinimizer.PropertySetter
 
set(Class<KEY>, VALUE) - Method in class edu.stanford.nlp.util.ArrayCoreMap
Associates the given value with the given type for future calls to get.
set(Class<KEY>, VALUE) - Method in class edu.stanford.nlp.util.HashableCoreMap
Sets the value associated with the given key; if the the key is one of the hashable keys, throws an exception.
set(int, int) - Method in class edu.stanford.nlp.util.IntTuple
 
set(double) - Method in class edu.stanford.nlp.util.MutableDouble
 
set(int) - Method in class edu.stanford.nlp.util.MutableInteger
 
set(Class<KEY>, VALUE) - Method in interface edu.stanford.nlp.util.TypesafeMap
Associates the given value with the given type for future calls to get.
setAfter(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the whitespace String after the word.
setAfter(String) - Method in interface edu.stanford.nlp.ling.HasContext
Set the whitespace String after the word.
setBatchSize(int) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
setBatchSize(int) - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
setBatchSize(int) - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
setBefore(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the whitespace String before the word.
setBefore(String) - Method in interface edu.stanford.nlp.ling.HasContext
Set the whitespace String before the word.
setBeginPosition(int) - Method in class edu.stanford.nlp.ling.CoreLabel
 
setBeginPosition(int) - Method in interface edu.stanford.nlp.ling.HasOffset
Set the beginning character offset for the label.
setBeginPosition(int) - Method in class edu.stanford.nlp.ling.StringLabel
 
setCapacity(int) - Method in class edu.stanford.nlp.util.ArrayCoreMap
 
setCategory(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the category value for the label (if one is stored).
setCategory(String) - Method in interface edu.stanford.nlp.ling.HasCategory
Set the category value for the label (if one is stored).
setColorChannels(boolean) - Method in class edu.stanford.nlp.util.logging.OutputHandler
 
setCount(E, double) - Method in class edu.stanford.nlp.stats.ClassicCounter
Sets the count for the given key to be the given value.
setCount(E, double) - Method in interface edu.stanford.nlp.stats.Counter
Sets the count for the given key to be the given value.
setCount(E, int) - Method in class edu.stanford.nlp.stats.IntCounter
Sets the current count for the given key.
setCount(E, String) - Method in class edu.stanford.nlp.stats.IntCounter
 
setCount(E, double) - Method in class edu.stanford.nlp.stats.IntCounter
 
setCount(K1, K2, double) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
setCount(K1, K2, double) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
setCounter(K1, Counter<K2>) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
replace the counter for K1-index o by new counter c
setCounts(Collection<E>, int) - Method in class edu.stanford.nlp.stats.IntCounter
Sets the current count for each of the given keys.
setDefaultReturnValue(double) - Method in class edu.stanford.nlp.stats.ClassicCounter
Sets the default return value.
setDefaultReturnValue(double) - Method in interface edu.stanford.nlp.stats.Counter
Sets the default return value.
setDefaultReturnValue(double) - Method in class edu.stanford.nlp.stats.IntCounter
 
setDefaultReturnValue(int) - Method in class edu.stanford.nlp.stats.IntCounter
 
setDocID(String) - Method in class edu.stanford.nlp.ling.CoreLabel
setDocID(String) - Method in interface edu.stanford.nlp.ling.HasIndex
 
setdot(double) - Method in class edu.stanford.nlp.math.DoubleAD
 
setEndPosition(int) - Method in class edu.stanford.nlp.ling.CoreLabel
 
setEndPosition(int) - Method in interface edu.stanford.nlp.ling.HasOffset
Set the ending character offset of the label (or -1 if none).
setEndPosition(int) - Method in class edu.stanford.nlp.ling.StringLabel
 
setEPS(double) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
setEpsilon(double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the epsilon value for LogConditionalObjectiveFunction.
setEpsilon(double) - Method in class edu.stanford.nlp.classify.LogPrior
 
setError() - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
setEvaluators(int, Evaluator[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
setEvaluators(int, Evaluator[]) - Method in interface edu.stanford.nlp.optimization.HasEvaluators
 
setEvaluators(int, Evaluator[]) - Method in class edu.stanford.nlp.optimization.HybridMinimizer
 
setEvaluators(int, Evaluator[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
setEvaluators(int, Evaluator[]) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
setEvaluators(int, Evaluator[]) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
setFirst(T1) - Method in class edu.stanford.nlp.util.Pair
 
setFirst(T1) - Method in class edu.stanford.nlp.util.Triple
 
setFromString(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the contents of this label to this String representing the complete contents of the label.
setFromString(String) - Method in interface edu.stanford.nlp.ling.Label
Set the contents of this label to this String representing the complete contents of the label.
setFromString(String) - Method in class edu.stanford.nlp.ling.StringLabel
Set the label from a String.
setFromString(String) - Method in class edu.stanford.nlp.ling.TaggedWord
Sets a TaggedWord from decoding the String passed in.
setFromString(String, String) - Method in class edu.stanford.nlp.ling.TaggedWord
 
setFromString(String) - Method in class edu.stanford.nlp.ling.ValueLabel
 
setFromString(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
The String is divided according to the divider character (usually, "/").
setFromString(String, String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
setFromString(String) - Method in class edu.stanford.nlp.ling.WordTag
Sets a WordTag from decoding the String passed in.
setFromString(String, String) - Method in class edu.stanford.nlp.ling.WordTag
 
setGlobal(Interner<Object>) - Static method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
For supplying a new instance for the global methods to use.
setGlobal(Interner<Object>) - Static method in class edu.stanford.nlp.util.Interner
For supplying a new instance for the global methods to use.
setHeldOutSearcher(LineSearcher) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Set the LineSearcher to be used in LinearClassifierFactory.heldOutSetSigma(GeneralDataset, GeneralDataset).
setHistory(List<double[]>, List<double[]>) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
setHistory(List<double[]>, List<double[]>) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
setIndex(int) - Method in class edu.stanford.nlp.ling.CoreLabel
setIndex(int) - Method in interface edu.stanford.nlp.ling.HasIndex
 
setLabel(LabelType) - Method in class edu.stanford.nlp.ling.BasicDatum
Removes all currently assigned Labels for this Datum then adds the given Label.
setLabel(L) - Method in class edu.stanford.nlp.ling.RVFDatum
Removes all currently assigned Labels for this Datum then adds the given Label.
setLabels(Collection<LabelType>) - Method in class edu.stanford.nlp.ling.BasicDatum
Removes all currently assigned labels for this Datum then adds all of the given Labels.
setLemma(String) - Method in class edu.stanford.nlp.ling.CoreLabel
 
setLemma(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
setM(int) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
setM(int) - Method in class edu.stanford.nlp.optimization.SQNMinimizer
 
setMap(Map<K1, V1>) - Method in class edu.stanford.nlp.util.MapFactory
A method to get a parameterized (genericized) map out.
setMap(Map<K1, V1>, int) - Method in class edu.stanford.nlp.util.MapFactory
 
setMaxTime(Long) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
setMem(int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Set the mem value for QNMinimizer.
setMinimizer(Minimizer<DiffFunction>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the minimizer.
setNER(String) - Method in class edu.stanford.nlp.ling.CoreLabel
 
setObject(T) - Method in class edu.stanford.nlp.util.ScoredObject
 
setOldOptions() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
setOriginalText(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the String which is the original character sequence of the token.
setOriginalText(String) - Method in interface edu.stanford.nlp.ling.HasContext
Set the String which is the original character sequence of the token.
setPrior(LogPrior) - Method in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
setPrior(LogPrior) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Set the prior.
setPrior(LogPrior) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
setPrior(LogPrior) - Method in class edu.stanford.nlp.classify.SemiSupervisedLogConditionalObjectiveFunction
 
setProperties(Properties) - Method in class edu.stanford.nlp.sequences.SeqClassifierFlags
Initialize this object using values in Properties object.
setProperties(Properties, boolean) - Method in class edu.stanford.nlp.sequences.SeqClassifierFlags
Initialize using values in Properties file.
setRetrainFromScratchAfterSigmaTuning(boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
If set to true, then when training a classifier, after an optimal sigma is chosen a model is relearned from scratch.
setRobustOptions() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
Sets - Class in edu.stanford.nlp.util
Utilities for sets.
setScore(double) - Method in class edu.stanford.nlp.util.ScoredObject
 
setSecond(T2) - Method in class edu.stanford.nlp.util.Pair
 
setSecond(T2) - Method in class edu.stanford.nlp.util.Triple
 
setSentIndex(int) - Method in class edu.stanford.nlp.ling.CoreLabel
setSentIndex(int) - Method in interface edu.stanford.nlp.ling.HasIndex
 
setSigma(double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
setSigma(double) - Method in class edu.stanford.nlp.classify.LogPrior
 
setSigmaSquared(double) - Method in class edu.stanford.nlp.classify.LogPrior
 
setSigmaSquaredM(double[]) - Method in class edu.stanford.nlp.classify.LogPrior
 
setSource(int) - Method in class edu.stanford.nlp.util.IntUni
 
setTag(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the tag value for the label (if one is stored).
setTag(String) - Method in interface edu.stanford.nlp.ling.HasTag
Set the tag value for the label (if one is stored).
setTag(String) - Method in class edu.stanford.nlp.ling.TaggedWord
 
setTag(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
Set the tag for the Label.
setTag(String) - Method in class edu.stanford.nlp.ling.WordTag
 
setThird(T3) - Method in class edu.stanford.nlp.util.Triple
 
setTol(double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Set the tolerance.
setTOL(double) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
setToLogDeterministic(float[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
setToLogDeterministic(double[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
setTuneSigmaCV(int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
setTuneSigmaCV sets the tuneSigmaCV flag: when turned on, the sigma is tuned by cross-validation.
setTuneSigmaCV(int) - Method in class edu.stanford.nlp.classify.NBLinearClassifierFactory
setTuneSigmaCV sets the tuneSigma flag: when turned on, the sigma is tuned by cross-validation.
setTuneSigmaHeldOut() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
setTuneSigmaHeldOut sets the tuneSigmaHeldOut flag: when turned on, the sigma is tuned by means of held-out (70%-30%).
setUseSum(boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
NOTE: nothing is actually done with this value! SetUseSum sets the useSum flag: when turned on, the Summed Conditional Objective Function is used.
setUseSumCondObjFun(boolean) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
setval(double) - Method in class edu.stanford.nlp.math.DoubleAD
 
setValue(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the value for the label (if one is stored).
setValue(String) - Method in interface edu.stanford.nlp.ling.Label
Set the value for the label (if one is stored).
setValue(String) - Method in class edu.stanford.nlp.ling.StringLabel
Set the value for the label.
setValue(String) - Method in class edu.stanford.nlp.ling.ValueLabel
Set the value for the label (if one is stored).
setValue(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
Set the value for the Label.
setValue(String) - Method in class edu.stanford.nlp.ling.WordTag
Set the value for the label (if one is stored).
setValue(double) - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
setValue(double) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
setVerbose(boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Set the verbose flag for CGMinimizer.
setWeights(double[][]) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
setWord(String) - Method in class edu.stanford.nlp.ling.CoreLabel
Set the word value for the label (if one is stored).
setWord(String) - Method in interface edu.stanford.nlp.ling.HasWord
Set the word value for the label (if one is stored).
setWord(String) - Method in class edu.stanford.nlp.ling.Word
 
setWord(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
setWord(String) - Method in class edu.stanford.nlp.ling.WordTag
 
SGD2QNhessSamples - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SGDMinimizer<T extends Function> - Class in edu.stanford.nlp.optimization
Stochastic Gradient Descent Minimizer The basic way to use the minimizer is with a null constructor, then the simple minimize method:

SGDMinimizer() - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDMinimizer(double, int) - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDMinimizer(double, int, int) - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDMinimizer(double, int, int, boolean) - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDMinimizer(double, int, int, long) - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDMinimizer(double, int, int, long, boolean) - Constructor for class edu.stanford.nlp.optimization.SGDMinimizer
 
SGDPasses - Variable in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
SGDPasses - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SGDToQNMinimizer - Class in edu.stanford.nlp.optimization
Stochastic Gradient Descent To Quasi Newton Minimizer An experimental minimizer which takes a stochastic function (one implementing AbstractStochasticCachingDiffFunction) and executes SGD for the first couple passes.
SGDToQNMinimizer(double, int, int, int) - Constructor for class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
SGDToQNMinimizer(double, int, int, int, int, int) - Constructor for class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
SGDToQNMinimizer(double, int, int, int, int, int, boolean) - Constructor for class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
shiftLeft() - Method in class edu.stanford.nlp.util.IntTuple
 
shortValue() - Method in class edu.stanford.nlp.util.MutableDouble
 
shortValue() - Method in class edu.stanford.nlp.util.MutableInteger
 
show() - Method in class edu.stanford.nlp.util.logging.Redwood.RedwoodChannels
Shows all of these channels.
showAll() - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Show all of the channels.
showAllChannels() - Static method in class edu.stanford.nlp.util.logging.Redwood
Show all channels.
showChannels(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Show multiple channels.
showOnlyChannels(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Show only the given channel.
showOnlyChannels(Object[]) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Show only the following channels.
shuffle(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
shuffle(int[], Random) - Static method in class edu.stanford.nlp.math.ArrayMath
 
shutUp() - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
shutUp() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.SGDToQNMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
shutUp() - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
sighanCorporaDict - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
for Sighan bakeoff 2005, the path to the dictionary of bigrams appeared in corpus
sighanPostProcessing - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
sigLevelByApproxRand(double[], double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Computes the significance level by approximate randomization, using a default value of 1000 iterations.
sigLevelByApproxRand(double[], double[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
Takes a pair of arrays, A and B, which represent corresponding outcomes of a pair of random variables: say, results for two different classifiers on a sequence of inputs.
sigLevelByApproxRand(int[], int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sigLevelByApproxRand(int[], int[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sigLevelByApproxRand(boolean[], boolean[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sigLevelByApproxRand(boolean[], boolean[], int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sigma - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
sigma - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
sigmasToTry - Static variable in class edu.stanford.nlp.classify.LinearClassifierFactory
 
sigmoid(double) - Static method in class edu.stanford.nlp.math.SloppyMath
Compute the sigmoid function with mean zero.
signalEndTrack(int) - Method in class edu.stanford.nlp.util.logging.LogRecordHandler
Signal the end of a track, i.e.
signalEndTrack(int) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Signal the end of a track, i.e.
signalEndTrack(int) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
Signal the end of a track, i.e.
signalEndTrack(int) - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Signal the end of a track, i.e.
signalShutdown() - Method in class edu.stanford.nlp.util.logging.LogRecordHandler
 
signalShutdown() - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
signalStartTrack(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.LogRecordHandler
Signal the start of a track, i.e.
signalStartTrack(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Signal the start of a track, i.e.
signalStartTrack(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.RepeatedRecordHandler
Signal the start of a track, i.e.
signalStartTrack(Redwood.Record) - Method in class edu.stanford.nlp.util.logging.VisibilityHandler
Signal the start of a track, i.e.
simpleGoodTuring(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Distribution
Creates a Distribution from the given counter using Gale & Sampsons' "simple Good-Turing" smoothing.
SimpleGoodTuring - Class in edu.stanford.nlp.stats
Simple Good-Turing smoothing, based on code from Sampson, available at: ftp://ftp.informatics.susx.ac.uk/pub/users/grs2/SGT.c

See also http://www.grsampson.net/RGoodTur.html

SimpleGoodTuring(int[], int[]) - Constructor for class edu.stanford.nlp.stats.SimpleGoodTuring
Each instance of this class encapsulates the computation of the smoothing for one probability distribution.
size - Variable in class edu.stanford.nlp.classify.GeneralDataset
 
size() - Method in class edu.stanford.nlp.classify.GeneralDataset
Returns the number of examples (Datums) in the Dataset.
size() - Method in class edu.stanford.nlp.objectbank.ObjectBank
Can be slow.
size() - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
size() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns the number of entries stored in this counter.
size() - Method in interface edu.stanford.nlp.stats.Counter
Returns the number of entries stored in this counter.
size() - Method in class edu.stanford.nlp.stats.IntCounter
 
size() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
size() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
size() - Method in class edu.stanford.nlp.util.ArrayCoreMap
Returns the number of elements in this map.
size() - Method in class edu.stanford.nlp.util.ArrayMap
 
size() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Get the number of elements in the queue.
size() - Method in class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
size() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Number of elements in the queue.
size() - Method in class edu.stanford.nlp.util.HashIndex
Returns the number of indexed objects.
size() - Method in interface edu.stanford.nlp.util.Index
Returns the number of indexed objects.
size() - Method in class edu.stanford.nlp.util.Interner
 
size() - Method in interface edu.stanford.nlp.util.TypesafeMap
Returns the number of keys in the map.
skewDivergence(Counter<E>, Counter<E>, double) - Static method in class edu.stanford.nlp.stats.Counters
Calculates the skew divergence between the two counters.
sList - Variable in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
sloppyGazette - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SloppyMath - Class in edu.stanford.nlp.math
The class SloppyMath contains methods for performing basic numeric operations.
slurpFile(File) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpFile(File, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpFile(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given file with the given encoding.
slurpFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given file
slurpFileNoExceptions(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given file with the given encoding.
slurpFileNoExceptions(File) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpFileNoExceptions(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpGBFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
slurpGBFileNoExceptions(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
slurpGBURL(URL) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpGBURLNoExceptions(URL) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpGZippedFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpGZippedFile(File) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text in the given File.
slurpReader(Reader) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text from the given Reader.
slurpURL(URL, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpURL(URL) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpURL(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpURLNoExceptions(URL, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpURLNoExceptions(URL) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
slurpURLNoExceptions(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns all the text at the given URL.
SMDMinimizer<T extends Function> - Class in edu.stanford.nlp.optimization
Stochastic Meta Descent Minimizer based on
SMDMinimizer() - Constructor for class edu.stanford.nlp.optimization.SMDMinimizer
 
SMDMinimizer(double, int, StochasticCalculateMethods, int) - Constructor for class edu.stanford.nlp.optimization.SMDMinimizer
 
SMDMinimizer(double, int, StochasticCalculateMethods, int, boolean) - Constructor for class edu.stanford.nlp.optimization.SMDMinimizer
 
smooth(List<double[]>) - Static method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
sorted(Iterable<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Return the items of an Iterable as a sorted list.
sorted(Iterable<T>, Comparator<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Return the items of an Iterable as a sorted list.
sortedIfPossible(Collection<T>) - Static method in class edu.stanford.nlp.util.ErasureUtils
 
splice(LogRecordHandler, LogRecordHandler, LogRecordHandler) - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a handler to as a child of an existing parent
spliceHandler(LogRecordHandler, LogRecordHandler, LogRecordHandler) - Static method in class edu.stanford.nlp.util.logging.Redwood
 
spliceHandler(LogRecordHandler, LogRecordHandler, Class<? extends LogRecordHandler>) - Static method in class edu.stanford.nlp.util.logging.Redwood
 
spliceHandler(Class<? extends LogRecordHandler>, LogRecordHandler, Class<? extends LogRecordHandler>) - Static method in class edu.stanford.nlp.util.logging.Redwood
 
split(double) - Method in class edu.stanford.nlp.classify.Dataset
 
split(int, int) - Method in class edu.stanford.nlp.classify.Dataset
 
split(int, int) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
split(double) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
split(double) - Method in class edu.stanford.nlp.classify.RVFDataset
 
split(int, int) - Method in class edu.stanford.nlp.classify.RVFDataset
 
split(String) - Static method in class edu.stanford.nlp.util.StringUtils
Splits on whitespace (\\s+).
split(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Splits the given string using the given regex as delimiters.
splitDocuments - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
splitOnCharWithQuoting(String, char, char, char) - Static method in class edu.stanford.nlp.util.StringUtils
This function splits the String s into multiple Strings using the splitChar.
splitOnHead - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
SQNMinimizer<T extends Function> - Class in edu.stanford.nlp.optimization
Online Limited-Memory Quasi-Newton BFGS implementation based on the algorithms in
SQNMinimizer(int) - Constructor for class edu.stanford.nlp.optimization.SQNMinimizer
 
SQNMinimizer() - Constructor for class edu.stanford.nlp.optimization.SQNMinimizer
 
SQNMinimizer(int, double, int, boolean) - Constructor for class edu.stanford.nlp.optimization.SQNMinimizer
 
standard() - Static method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
The default Redwood configuration, which prints to the console.
standardDeviation(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
standardErrorOfMean(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
standardize(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Standardize values in this array, i.e., subtract the mean and divide by the standard deviation.
start(double, double[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
start(double, double[], double[]) - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
 
start() - Method in class edu.stanford.nlp.util.Timing
Start timer.
start_track(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
startDoing(String) - Static method in class edu.stanford.nlp.util.Timing
Print the start of timing message to stderr and start the timer.
startFold - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
startThreads(String) - Static method in class edu.stanford.nlp.util.logging.Redwood
Start a multithreaded logging environment.
startThreads(String) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
startTime() - Static method in class edu.stanford.nlp.util.Timing
Start (static) timer.
startTrack(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood
Begin a "track;" that is, begin logging at one level deeper.
startTrack(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
state - Variable in class edu.stanford.nlp.classify.CrossValidator.SavedState
 
STDERR - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
STDERR - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
stderr() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a console pipeline to the Redwood handler tree, printing to stderr.
stdev(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
STDOUT - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
STDOUT - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
stdout() - Method in class edu.stanford.nlp.util.logging.RedwoodConfiguration
Add a console pipeline to the Redwood handler tree, printing to stdout.
stem(Word) - Method in class edu.stanford.nlp.process.Morphology
 
stem(String) - Method in class edu.stanford.nlp.process.Morphology
 
stem(CoreLabel) - Method in class edu.stanford.nlp.process.Morphology
Adds the LemmaAnnotation to the given CoreLabel.
stem(CoreLabel, Class<? extends CoreAnnotation<String>>) - Method in class edu.stanford.nlp.process.Morphology
Adds annotation ann to the given CoreLabel.
stemStatic(String, String) - Static method in class edu.stanford.nlp.process.Morphology
Return a new WordTag which has the lemma as the value of word().
stemStatic(WordTag) - Static method in class edu.stanford.nlp.process.Morphology
Return a new WordTag which has the lemma as the value of word().
stemStaticSynchronized(String, String) - Static method in class edu.stanford.nlp.process.Morphology
 
stochasticBatchSize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
StochasticCalculateMethods - Enum in edu.stanford.nlp.optimization
This enumeratin was created to organize the selection of different methods for stochastic calculations.
StochasticDiffFunctionTester - Class in edu.stanford.nlp.optimization
 
StochasticDiffFunctionTester(Function) - Constructor for class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
StochasticInPlaceMinimizer<T extends Function> - Class in edu.stanford.nlp.optimization
In place Stochastic Gradient Descent Minimizer.
StochasticInPlaceMinimizer(double, int) - Constructor for class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
StochasticInPlaceMinimizer(double, int, int) - Constructor for class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
StochasticInPlaceMinimizer(LogPrior, int, int, int) - Constructor for class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
StochasticInPlaceMinimizer.InvalidElementException - Class in edu.stanford.nlp.optimization
 
StochasticInPlaceMinimizer.InvalidElementException(String) - Constructor for class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer.InvalidElementException
 
stochasticMethod - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
StochasticMinimizer<T extends Function> - Class in edu.stanford.nlp.optimization
Stochastic Gradient Descent Minimizer.
StochasticMinimizer() - Constructor for class edu.stanford.nlp.optimization.StochasticMinimizer
 
StochasticMinimizer.InvalidElementException - Class in edu.stanford.nlp.optimization
 
StochasticMinimizer.InvalidElementException(String) - Constructor for class edu.stanford.nlp.optimization.StochasticMinimizer.InvalidElementException
 
StochasticMinimizer.PropertySetter<T1> - Interface in edu.stanford.nlp.optimization
 
stop() - Static method in class edu.stanford.nlp.util.logging.Redwood
Stop Redwood, closing all tracks and prohibiting future log messages.
stop() - Method in class edu.stanford.nlp.util.Timing
Stop timer.
stop(String, PrintStream) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time and stop timer.
stop(String) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time to System.err and stop timer.
stop(String, PrintWriter) - Method in class edu.stanford.nlp.util.Timing
Print elapsed time and stop timer.
StreamGobbler - Class in edu.stanford.nlp.util
Reads the output of a process started by Process.exec() Adapted from: http://www.velocityreviews.com/forums/t130884-process-runtimeexec-causes-subprocess-hang.html
StreamGobbler(InputStream, Writer) - Constructor for class edu.stanford.nlp.util.StreamGobbler
 
strictlyFirstOrder - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
strictlySecondOrder - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
strictlyThirdOrder - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
strictlyZeroethOrder - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
stringFromFile(String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns the contents of a file as a single string.
stringFromFile(String, String) - Static method in class edu.stanford.nlp.io.IOUtils
Returns the contents of a file as a single string.
stringIntern(Pair<String, String>) - Static method in class edu.stanford.nlp.util.Pair
If first and second are Strings, then this returns an MutableInternedPair where the Strings have been interned, and if this Pair is serialized and then deserialized, first and second are interned upon deserialization.
StringLabel - Class in edu.stanford.nlp.ling
A StringLabel object acts as a Label by containing a single String, which it sets or returns in response to requests.
StringLabel() - Constructor for class edu.stanford.nlp.ling.StringLabel
Create a new StringLabel with a null content (i.e., str).
StringLabel(String) - Constructor for class edu.stanford.nlp.ling.StringLabel
Create a new StringLabel with the given content.
StringLabel(String, int, int) - Constructor for class edu.stanford.nlp.ling.StringLabel
Create a new StringLabel with the given content.
StringLabel(Label) - Constructor for class edu.stanford.nlp.ling.StringLabel
Create a new StringLabel with the value() of another label as its label.
StringLabelFactory - Class in edu.stanford.nlp.ling
A StringLabelFactory object makes a simple StringLabel out of a String.
StringLabelFactory() - Constructor for class edu.stanford.nlp.ling.StringLabelFactory
 
stringToProperties(String) - Static method in class edu.stanford.nlp.util.StringUtils
This method converts a comma-separated String (with whitespace optionally allowed after the comma) representing properties to a Properties object.
stringToProperties(String, Properties) - Static method in class edu.stanford.nlp.util.StringUtils
This method updates a Properties object based on a comma-separated String (with whitespace optionally allowed after the comma) representing properties to a Properties object.
stringToSet(String, String) - Static method in class edu.stanford.nlp.util.StringUtils
 
StringUtils - Class in edu.stanford.nlp.util
StringUtils is a class for random String things, including output formatting and command line argument parsing.
stripNonAlphaNumerics(String) - Static method in class edu.stanford.nlp.util.StringUtils
 
stripSGML(String) - Static method in class edu.stanford.nlp.util.StringUtils
 
style(StringBuilder, String, Color, Style) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Style a particular String segment, according to a color and style
Style - Enum in edu.stanford.nlp.util.logging
ANSI supported styles (rather, a subset of) These values are mirrored in Redwood.Util
styleChannel(String, Style) - Method in class edu.stanford.nlp.util.logging.OutputHandler
Style the tag for a particular channel this style
subArray(int[], int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
 
subCWGaz - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
subtractAll(IntCounter<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Subtracts the counts in the given Counter from the counts in this Counter.
subtractAll(K1, Counter<K2>) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
subtractAll(TwoDimensionalCounterInterface<K1, K2>, boolean) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
subtractInPlace(Counter<E>, Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of target to be target[k]-arg[k] for all keys k in target.
subtractInPlace(double[], Counter<E>, Index<E>) - Static method in class edu.stanford.nlp.stats.Counters
Sets each value of double[] target to be target[idx.indexOf(k)]-a.getCount(k) for all keys k in arg
sum(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the sum of an array of numbers.
sum(double[], int, int) - Static method in class edu.stanford.nlp.math.ArrayMath
Returns the sum of the portion of an array of numbers between fromIndex, inclusive, and toIndex, exclusive.
sum(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sum(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sum(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sumEntries(Counter<E>, Collection<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
sumInnerCounter() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
Returns the counters with keys as the first key and count as the total count of the inner counter for that key
summaryStatistics() - Method in class edu.stanford.nlp.classify.Dataset
Prints some summary statistics to stderr for the Dataset.
summaryStatistics() - Method in class edu.stanford.nlp.classify.GeneralDataset
Print some statistics summarizing the dataset
summaryStatistics() - Method in class edu.stanford.nlp.classify.RVFDataset
Prints some summary statistics to stderr for the Dataset.
sums - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
sumSquared(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
sumSquaredError(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
supportsAnsi() - Static method in class edu.stanford.nlp.util.logging.Redwood
 
suppressMidDotPostprocessing - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
svmLightLineToDatum(String) - Static method in class edu.stanford.nlp.classify.Dataset
 
svmLightLineToRVFDatum(String) - Static method in class edu.stanford.nlp.classify.RVFDataset
 
svmModelFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
symmetricDiff(Set<E>, Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns the symmetric difference of sets s1 and s2 (i.e.
SynchronizedInterner<T> - Class in edu.stanford.nlp.util.concurrent
For interning (canonicalizing) things in a multi-threaded environment.
SynchronizedInterner(Interner<T>) - Constructor for class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 
SynchronizedInterner(Interner<T>, Object) - Constructor for class edu.stanford.nlp.util.concurrent.SynchronizedInterner
 

T

t0 - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
tab - Variable in class edu.stanford.nlp.util.logging.OutputHandler
The tab character
tag() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the tag value of the label (or null if none).
tag() - Method in interface edu.stanford.nlp.ling.HasTag
Return the tag value of the label (or null if none).
tag() - Method in class edu.stanford.nlp.ling.TaggedWord
 
tag() - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
tag() - Method in class edu.stanford.nlp.ling.WordTag
 
TAG_LABEL - Static variable in class edu.stanford.nlp.ling.TaggedWordFactory
 
TAG_LABEL - Static variable in class edu.stanford.nlp.ling.WordLemmaTagFactory
 
TAG_SEPARATOR - Static variable in class edu.stanford.nlp.ling.CoreLabel
Tag separator to use by default
TaggedWord - Class in edu.stanford.nlp.ling
A TaggedWord object contains a word and its tag.
TaggedWord() - Constructor for class edu.stanford.nlp.ling.TaggedWord
Create a new TaggedWord.
TaggedWord(String) - Constructor for class edu.stanford.nlp.ling.TaggedWord
Create a new TaggedWord.
TaggedWord(String, String) - Constructor for class edu.stanford.nlp.ling.TaggedWord
Create a new TaggedWord.
TaggedWord(Label) - Constructor for class edu.stanford.nlp.ling.TaggedWord
Create a new TaggedWord.
TaggedWord(Label, Label) - Constructor for class edu.stanford.nlp.ling.TaggedWord
Create a new TaggedWord.
TaggedWordFactory - Class in edu.stanford.nlp.ling
A TaggedWordFactory acts as a factory for creating objects of class TaggedWord.
TaggedWordFactory() - Constructor for class edu.stanford.nlp.ling.TaggedWordFactory
Create a new TaggedWordFactory.
TaggedWordFactory(char) - Constructor for class edu.stanford.nlp.ling.TaggedWordFactory
Create a new TaggedWordFactory.
takeStep(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
takeStep(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
takeStep(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
takeStep(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.SQNMinimizer
 
takeStep(AbstractStochasticCachingDiffFunction) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
terminateOnAverageImprovement(boolean) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
terminateOnNumericalZero(boolean) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
terminateOnRelativeNorm(boolean) - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
testBatchSize - Variable in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
testConditionNumber(int) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
testDerivatives(double[], double) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
This function tests to make sure that the sum of the stochastic calculated gradients is equal to the full gradient.
testDirs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
testFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
testFiles - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
testHessSamples - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
testObjFunction - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
testSumOfBatches(double[], double) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
This function tests to make sure that the sum of the stochastic calculated gradients is equal to the full gradient.
testVariance(double[]) - Method in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
testVariance - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
TEXT_SERIALIZATION_DELIMITER - Static variable in class edu.stanford.nlp.classify.LinearClassifier
 
textFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tfLogScale(C, double) - Static method in class edu.stanford.nlp.stats.Counters
Returns a new Counter which is the input counter with log tf scaling
third - Variable in class edu.stanford.nlp.util.Triple
 
third() - Method in class edu.stanford.nlp.util.Triple
 
thisBatch - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
thisFunc - Variable in class edu.stanford.nlp.optimization.StochasticDiffFunctionTester
 
thread - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
thread(String, Iterable<R>) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
Wrap a collection of threads (Runnables) to be logged by Redwood.
thread(Iterable<R>) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
threadAndRun(String, Iterable<R>, int) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
Thread a collection of runnables, and run them via a java Executor.
threadAndRun(String, Iterable<R>) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
threadAndRun(Iterable<R>, int) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
threadAndRun(Iterable<R>) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
tick() - Static method in class edu.stanford.nlp.util.Timing
Restart (static) timer.
tick(String, PrintStream) - Static method in class edu.stanford.nlp.util.Timing
Print elapsed time and restart (static) timer.
tick(String) - Static method in class edu.stanford.nlp.util.Timing
Print elapsed time to System.err and restart (static) timer.
timesstamp - Variable in class edu.stanford.nlp.util.logging.Redwood.Record
 
Timing - Class in edu.stanford.nlp.util
A class for measuring how long things take.
Timing() - Constructor for class edu.stanford.nlp.util.Timing
Constructs new Timing object and starts the timer.
timitDatum - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
to1D(double[][]) - Method in class edu.stanford.nlp.classify.AdaptedGaussianPriorObjectiveFunction
 
to2D(double[]) - Method in class edu.stanford.nlp.classify.BiasedLogConditionalObjectiveFunction
 
to2D(double[]) - Method in class edu.stanford.nlp.classify.GeneralizedExpectationObjectiveFunction
 
to2D(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
to2D(double[], int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
to2D(double[], int, int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
to3D(double[]) - Method in class edu.stanford.nlp.classify.LogConditionalEqConstraintFunction
 
toAllWeightsString() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
toArray() - Method in class edu.stanford.nlp.objectbank.ObjectBank
Can be slow.
toArray(T[]) - Method in class edu.stanford.nlp.objectbank.ObjectBank
Can be slow.
toArray(T[]) - Method in interface edu.stanford.nlp.util.Index
 
toAscii(String) - Static method in class edu.stanford.nlp.util.StringUtils
 
toBiggestValuesFirstString(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
toBiggestValuesFirstString(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
 
toBiggestValuesFirstString(Counter<Integer>, int, Index<T>) - Static method in class edu.stanford.nlp.stats.Counters
 
toBiggestWeightFeaturesString(boolean, int, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifier
Return a String that prints features with large weights.
toBinaryString(byte[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toComparator(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a comparator backed by this counter: two objects are compared by their associated values stored in the counter.
toComparator(Counter<E>, boolean, boolean) - Static method in class edu.stanford.nlp.stats.Counters
Returns a comparator suitable for sorting this Counter's keys or entries by their respective value or magnitude (by absolute value).
toComparatorDescending(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a comparator backed by this counter: two objects are compared by their associated values stored in the counter.
toComparatorWithKeys(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a comparator backed by this counter: two objects are compared by their associated values stored in the counter.
toContinue() - Method in class edu.stanford.nlp.optimization.QNMinimizer.Record
This function checks for convergence through first order optimality, numerical convergence (i.e., zero numerical gradient), and also by checking the average improvement.
toCounter(double[], Index<T>) - Static method in class edu.stanford.nlp.stats.Counters
 
toCounter(Map<Integer, ? extends Number>, Index<E>) - Static method in class edu.stanford.nlp.stats.Counters
Turns the given map and index into a counter instance.
toCSVString(NumberFormat) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
toCSVString(NumberFormat) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
toCSVString(String[]) - Static method in class edu.stanford.nlp.util.StringUtils
 
toDescendingMagnitudeSortedListWithCounts(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
toDistributionString(int) - Method in class edu.stanford.nlp.classify.LinearClassifier
Similar to histogram but exact values of the weights to see whether there are many equal weights.
toDouble(float[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Casts to a double array
toDouble(int[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
Casts to a double array.
toHistogramString() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
toInterval(E, E) - Static method in class edu.stanford.nlp.util.Interval
Create an interval with the specified endpoints in the specified order, Returns null if a does not come before b (invalid interval)
toInterval(E, E, int) - Static method in class edu.stanford.nlp.util.Interval
Create an interval with the specified endpoints in the specified order, using the specified flags.
toInvocationString(String, String[]) - Static method in class edu.stanford.nlp.util.StringUtils
 
tokenFactory - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tokenizerOptions - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tokensAnnotationClassName - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tolerance - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
toList(Iterable<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Create a list out of the items in the Iterable.
toMatrix(List<K1>, List<K2>) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
Given an ordering of the first (row) and second (column) keys, will produce a double matrix.
toMatrix(List<K1>, List<K2>) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
Given an ordering of the first (row) and second (column) keys, will produce a double matrix.
toMatrixString(int) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
toMatrixString(int) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
topFeaturesToString(List<Triple<F, L, Double>>) - Method in class edu.stanford.nlp.classify.LinearClassifier
Returns string representation of a list of top features
toPrimitive(Long[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Integer[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Short[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Character[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Double[]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Long[], long) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Integer[], int) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Short[], short) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Character[], char) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPrimitive(Double[], double) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toPriorityQueue(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Returns a PriorityQueue whose elements are the keys of Counter c, and the score of each key in c becomes its priority.
toRankCounter(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
Converts a counter to ranks
toRelFlags(int, int) - Method in class edu.stanford.nlp.util.Interval
 
toSecondsString() - Method in class edu.stanford.nlp.util.Timing
 
toSecondsString(long) - Static method in class edu.stanford.nlp.util.Timing
 
toSet(Iterable<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Create a set out of the items in the Iterable.
toShorterString(String...) - Method in class edu.stanford.nlp.util.ArrayCoreMap
 
toSortedByKeysString(Counter<T>, String, String, String) - Static method in class edu.stanford.nlp.stats.Counters
Returns a string representation of a Counter, where (key, value) pairs are sorted by key, and formatted as specified.
toSortedList(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
A List of the keys in c, sorted from highest count to lowest.
toSortedList() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
toSortedList() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
 
toSortedList() - Method in interface edu.stanford.nlp.util.PriorityQueue
 
toSortedListKeyComparable(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
A List of the keys in c, sorted from highest count to lowest.
toSortedListWithCounts(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
A List of the keys in c, sorted from highest count to lowest, paired with counts
toSortedString(Counter<T>, int, String, String, String) - Static method in class edu.stanford.nlp.stats.Counters
Returns a string representation of a Counter, displaying the keys and their counts in decreasing order of count.
toSortedString(Counter<T>, int, String, String) - Static method in class edu.stanford.nlp.stats.Counters
Returns a string representation of a Counter, displaying the keys and their counts in decreasing order of count.
toString() - Method in class edu.stanford.nlp.classify.Dataset
 
toString() - Method in class edu.stanford.nlp.classify.LinearClassifier
Print out a partial representation of a linear classifier.
toString(String, int) - Method in class edu.stanford.nlp.classify.LinearClassifier
Print out a partial representation of a linear classifier in one of several ways.
toString() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
toString() - Method in class edu.stanford.nlp.classify.RVFDataset
 
toString() - Method in class edu.stanford.nlp.ling.BasicDatum
Returns a String representation of this BasicDatum (lists features and labels).
toString() - Method in interface edu.stanford.nlp.ling.Label
Return a String representation of the label.
toString() - Method in class edu.stanford.nlp.ling.RVFDatum
Returns a String representation of this BasicDatum (lists features and labels).
toString() - Method in class edu.stanford.nlp.ling.StringLabel
 
toString() - Method in class edu.stanford.nlp.ling.TaggedWord
 
toString(String) - Method in class edu.stanford.nlp.ling.TaggedWord
 
toString() - Method in class edu.stanford.nlp.ling.ValueLabel
Return a string representation of the label.
toString() - Method in class edu.stanford.nlp.ling.WordLemmaTag
Return a String representation of the Label.
toString(String) - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
toString() - Method in class edu.stanford.nlp.ling.WordTag
Return a String representation of the label.
toString(String) - Method in class edu.stanford.nlp.ling.WordTag
 
toString(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(double[], NumberFormat) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(float[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(float[], NumberFormat) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(int[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(int[], NumberFormat) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(byte[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(byte[], NumberFormat) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(int[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(int[][], Object[], Object[], int, int, NumberFormat, boolean) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(double[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(double[][], int, Object[], Object[], NumberFormat, boolean) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(float[][]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString(float[][], int, Object[], Object[], NumberFormat, boolean) - Static method in class edu.stanford.nlp.math.ArrayMath
 
toString() - Method in class edu.stanford.nlp.math.DoubleAD
 
toString() - Method in class edu.stanford.nlp.sequences.SeqClassifierFlags
Print the properties specified by this object.
toString() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns a String representation of the Counter, as formatted by the underlying Map.
toString(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
Returns a string representation which includes no more than the maxKeysToPrint elements with largest counts.
toString(Counter<E>, NumberFormat) - Static method in class edu.stanford.nlp.stats.Counters
 
toString(Counter<E>, NumberFormat, String, String, String, String) - Static method in class edu.stanford.nlp.stats.Counters
Pretty print a Counter.
toString(NumberFormat) - Method in class edu.stanford.nlp.stats.Distribution
 
toString() - Method in class edu.stanford.nlp.stats.Distribution
 
toString() - Method in class edu.stanford.nlp.stats.IntCounter
 
toString(NumberFormat, String, String, String, String) - Method in class edu.stanford.nlp.stats.IntCounter
 
toString(NumberFormat) - Method in class edu.stanford.nlp.stats.IntCounter
 
toString() - Method in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
toString() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
A simple String representation of this TwoDimensionalCounter, which has the String representation of each key pair on a separate line, followed by the count for that pair.
toString() - Method in class edu.stanford.nlp.util.ArrayCoreMap
 
toString(int[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toString(boolean[][]) - Static method in class edu.stanford.nlp.util.ArrayUtils
 
toString() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
toString(int) - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
Returns a representation of the queue in decreasing priority order, displaying at most maxKeysToPring elements.
toString() - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns a representation of the queue in decreasing priority order.
toString(int) - Method in class edu.stanford.nlp.util.FixedPrioritiesPriorityQueue
Returns a representation of the queue in decreasing priority order, displaying at most maxKeysToPring elements.
toString() - Method in class edu.stanford.nlp.util.HashIndex
Returns a readable version of the Index contents
toString(int) - Method in class edu.stanford.nlp.util.HashIndex
Returns a readable version of at least part of the Index contents.
toString() - Method in class edu.stanford.nlp.util.IntTuple
 
toString() - Method in class edu.stanford.nlp.util.logging.Redwood.Record
 
toString() - Method in class edu.stanford.nlp.util.logging.Redwood.RecordHandlerTree
 
toString() - Method in class edu.stanford.nlp.util.MetaClass.ClassFactory
 
toString() - Method in class edu.stanford.nlp.util.MetaClass
 
toString() - Method in class edu.stanford.nlp.util.MutableDouble
 
toString() - Method in class edu.stanford.nlp.util.MutableInteger
 
toString() - Method in class edu.stanford.nlp.util.Pair
 
toString(int) - Method in interface edu.stanford.nlp.util.PriorityQueue
Returns a representation of the queue in decreasing priority order, displaying at most maxKeysToPring elements.
toString() - Method in class edu.stanford.nlp.util.ScoredComparator
 
toString() - Method in class edu.stanford.nlp.util.ScoredObject
 
toString() - Method in class edu.stanford.nlp.util.Timing
 
toString() - Method in class edu.stanford.nlp.util.Triple
 
toStringArr(int[]) - Static method in class edu.stanford.nlp.stats.AccuracyStats
 
toStringOneEntryPerLine() - Method in class edu.stanford.nlp.util.HashIndex
 
toStringOneEntryPerLine(int) - Method in class edu.stanford.nlp.util.HashIndex
 
toSummaryStatistics() - Method in class edu.stanford.nlp.classify.Dataset
 
toSummaryString() - Method in class edu.stanford.nlp.classify.Dataset
 
toSummaryString() - Method in class edu.stanford.nlp.classify.RVFDataset
 
totalCount() - Method in class edu.stanford.nlp.stats.ClassicCounter
Computes the total of all counts in this counter, and returns it as a double.
totalCount() - Method in interface edu.stanford.nlp.stats.Counter
Computes the total of all counts in this counter, and returns it as a double.
totalCount() - Method in class edu.stanford.nlp.stats.Distribution
 
totalCount(Filter<E>) - Method in class edu.stanford.nlp.stats.IntCounter
 
totalCount() - Method in class edu.stanford.nlp.stats.IntCounter
 
totalCount() - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
Takes linear time.
totalCount(K1) - Method in class edu.stanford.nlp.stats.TwoDimensionalCounter
 
totalCount() - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
totalCount(K1) - Method in interface edu.stanford.nlp.stats.TwoDimensionalCounterInterface
 
totalDoubleCount() - Method in class edu.stanford.nlp.stats.IntCounter
 
totalDoubleCount(Filter<E>) - Method in class edu.stanford.nlp.stats.IntCounter
 
totalIntCount() - Method in class edu.stanford.nlp.stats.IntCounter
Returns the current total count for all objects in this Counter.
totalIntCount(Filter<E>) - Method in class edu.stanford.nlp.stats.IntCounter
Returns the total count for all objects in this Counter that pass the given Filter.
totalSize() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
toValidInterval(E, E) - Static method in class edu.stanford.nlp.util.Interval
Create an interval with the specified endpoints, reordering them as needed
toValidInterval(E, E, int) - Static method in class edu.stanford.nlp.util.Interval
Create an interval with the specified endpoints, reordering them as needed, using the specified flags
toVerticalString(Counter<E>) - Static method in class edu.stanford.nlp.stats.Counters
 
toVerticalString(Counter<E>, int) - Static method in class edu.stanford.nlp.stats.Counters
 
toVerticalString(Counter<E>, String) - Static method in class edu.stanford.nlp.stats.Counters
 
toVerticalString(Counter<E>, int, String) - Static method in class edu.stanford.nlp.stats.Counters
 
toVerticalString(Counter<E>, int, String, boolean) - Static method in class edu.stanford.nlp.stats.Counters
Returns a String representation of the k keys with the largest counts in the given Counter, using the given format string.
toVerticalString() - Method in class edu.stanford.nlp.util.BinaryHeapPriorityQueue
 
toVerticalString(Map<K, V>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
tr(String, String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Swap any occurrences of any characters in the from String in the input String with the corresponding character from the to String.
trackColor - Variable in class edu.stanford.nlp.util.logging.OutputHandler
The color to use for track beginning and ends
trackStack - Variable in class edu.stanford.nlp.util.logging.OutputHandler
Information about the current and higher level tracks
trackStyle - Variable in class edu.stanford.nlp.util.logging.OutputHandler
The style to use for track beginning and ends
train(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
train(GeneralDataset<L, F>, double, double) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
trainClassifier(List<RVFDatum<L, F>>) - Method in class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
 
trainClassifier(Collection<Datum<L, F>>) - Method in class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
Takes a Collection of Datum objects and gives you back a Classifier trained on it.
trainClassifier(Reference<Collection<Datum<L, F>>>) - Method in class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
Takes a Reference to a Collection of Datum objects and gives you back a Classifier trained on them
trainClassifier(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
Trains a Classifier on a Dataset.
trainClassifier(List<RVFDatum<L, F>>) - Method in interface edu.stanford.nlp.classify.ClassifierFactory
Deprecated. 
trainClassifier(GeneralDataset<L, F>) - Method in interface edu.stanford.nlp.classify.ClassifierFactory
 
trainClassifier(Iterable<Datum<L, F>>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, float[], LogPrior) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainClassifier(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainClassifier(List<RVFDatum<L, F>>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Deprecated. 
trainClassifier(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, LogPrior, boolean) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double, double) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double, double, LogPrior) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double, double, boolean) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(GeneralDataset<L, F>, double, double, LogPrior, boolean) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainClassifier(List<RVFDatum<L, F>>) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
Deprecated. 
trainClassifier(List<RVFDatum<L, F>>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
Deprecated. 
trainClassifier(List<RVFDatum<L, F>>, Set<F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
The examples are assumed a list of RFVDatum the datums are assumed to not contain the zeros and then they are added to each instance
trainClassifier(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
trainClassifierSemiSup(GeneralDataset<L, F>, GeneralDataset<L, F>, double[][], double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
IMPORTANT: dataset and biasedDataset must have same featureIndex, labelIndex
trainClassifierV(GeneralDataset<L, F>, GeneralDataset<L, F>, double, double, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Train a classifier with a sigma tuned on a validation set.
trainClassifierV(GeneralDataset<L, F>, double, double, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Train a classifier with a sigma tuned on a validation set.
trainDirs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
trainFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
trainFileList - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
trainFiles - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
trainHierarchical - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
trainSemiSupGE(GeneralDataset<L, F>, List<? extends Datum<L, F>>, List<F>, double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Trains the linear classifier using Generalized Expectation criteria as described in Generalized Expectation Criteria for Semi Supervised Learning of Conditional Random Fields, Mann and McCallum, ACL 2008.
trainSemiSupGE(GeneralDataset<L, F>, List<? extends Datum<L, F>>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Trains the linear classifier using Generalized Expectation criteria as described in Generalized Expectation Criteria for Semi Supervised Learning of Conditional Random Fields, Mann and McCallum, ACL 2008.
trainSemiSupGE(GeneralDataset<L, F>, List<? extends Datum<L, F>>, double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainTestFoldsForCV(List<T>, int) - Static method in class edu.stanford.nlp.util.CollectionUtils
Split a list into train, test pairs for use in k-fold crossvalidation.
trainWeightedData(GeneralDataset<L, F>, float[]) - Method in class edu.stanford.nlp.classify.LogisticClassifier
Deprecated. 
trainWeightedData(GeneralDataset<L, F>, float[]) - Method in class edu.stanford.nlp.classify.LogisticClassifierFactory
 
trainWeights(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.AbstractLinearClassifierFactory
 
trainWeights(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainWeights(GeneralDataset<L, F>, double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainWeights(GeneralDataset<L, F>, double[], boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
trainWeights(GeneralDataset<L, F>) - Method in class edu.stanford.nlp.classify.NBLinearClassifierFactory
 
trainWeightsSemiSup(GeneralDataset<L, F>, GeneralDataset<L, F>, double[][], double[]) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
transferSigmas - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
transform(Counter<T1>, Function<T1, T2>) - Static method in class edu.stanford.nlp.stats.Counters
Returns the counter with keys modified according to function F.
TREE_SET_FACTORY - Static variable in class edu.stanford.nlp.util.CollectionFactory
 
treeMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns an TreeMap.
treeSetFactory() - Static method in class edu.stanford.nlp.util.CollectionFactory
 
trim(String, int) - Static method in class edu.stanford.nlp.util.StringUtils
Returns s if it's at most maxWidth chars, otherwise chops right side to fit.
trim(Object, int) - Static method in class edu.stanford.nlp.util.StringUtils
 
trimData() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
trimLabels() - Method in class edu.stanford.nlp.classify.GeneralDataset
 
trimToSize(int[]) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
trimToSize(int[][]) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
trimToSize(double[][]) - Method in class edu.stanford.nlp.classify.GeneralDataset
 
Triple<T1,T2,T3> - Class in edu.stanford.nlp.util
Class representing an ordered triple of objects, possibly typed.
Triple(T1, T2, T3) - Constructor for class edu.stanford.nlp.util.Triple
 
truncate(int, int, int) - Static method in class edu.stanford.nlp.util.StringUtils
This returns a string from decimal digit smallestDigit to decimal digit biggest digit.
tryEta(AbstractStochasticCachingDiffUpdateFunction, double[], int[], double) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
tune(Function, double[], long) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
tune(Function, double[], long, double, double) - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
tune(Function, double[], long) - Method in class edu.stanford.nlp.optimization.SGDMinimizer
 
tune(Function, double[], long) - Method in class edu.stanford.nlp.optimization.SMDMinimizer
 
tune(Function, double[], long) - Method in class edu.stanford.nlp.optimization.SQNMinimizer
 
tune(AbstractStochasticCachingDiffUpdateFunction, double[], int, double) - Method in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
Finds a good learning rate to start with.
tune(Function, double[], long) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tune(Function, double[], long, List<Integer>, List<Double>) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tuneBatch(Function, double[], long, int) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tuneDouble(Function, double[], long, StochasticMinimizer.PropertySetter<Double>, double, double) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tuneDouble(Function, double[], long, StochasticMinimizer.PropertySetter<Double>, double, double, double) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tuneFixedGain(Function, double[], long, double) - Method in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 
tuneGain(Function, double[], long, double, double) - Method in class edu.stanford.nlp.optimization.StochasticMinimizer
 
tuneSampleSize - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tuneSGD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
tuningSamples - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
TwoDimensionalCounter<K1,K2> - Class in edu.stanford.nlp.stats
A class representing a mapping between pairs of typed objects and double values.
TwoDimensionalCounter() - Constructor for class edu.stanford.nlp.stats.TwoDimensionalCounter
 
TwoDimensionalCounter(MapFactory<K1, ClassicCounter<K2>>, MapFactory<K2, MutableDouble>) - Constructor for class edu.stanford.nlp.stats.TwoDimensionalCounter
 
TwoDimensionalCounterInterface<K1,K2> - Interface in edu.stanford.nlp.stats
Interface representing a mapping between pairs of typed objects and double values.
twoStage - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
type - Variable in class edu.stanford.nlp.classify.LogPrior
 
type - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
TypesafeMap<BASE> - Interface in edu.stanford.nlp.util
Type signature for a class that supports the basic operations required of a typesafe heterogeneous map.
TypesafeMap.Key<BASE,VALUE> - Interface in edu.stanford.nlp.util
Base type of keys for the map.

U

UCL - Static variable in class edu.stanford.nlp.classify.NaiveBayesClassifierFactory
 
unbox(Collection<Double>) - Static method in class edu.stanford.nlp.math.ArrayMath
 
unboxToInt(Collection<Integer>) - Static method in class edu.stanford.nlp.math.ArrayMath
 
uncheckedCast(Object) - Static method in class edu.stanford.nlp.util.ErasureUtils
Casts an Object to a T
UNDERLINE - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
union(C, C) - Static method in class edu.stanford.nlp.stats.Counters
Returns a Counter that is the union of the two Counters passed in (counts are added).
union(Collection<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
union(Set<E>, Set<E>) - Static method in class edu.stanford.nlp.util.Sets
Returns the union of sets s1 and s2.
unionAsSet(Collection<T>, Collection<T>) - Static method in class edu.stanford.nlp.util.CollectionUtils
 
uniqueNonhashableObjects(Collection<ObjType>, Function<ObjType, Hashable>) - Static method in class edu.stanford.nlp.util.CollectionUtils
Makes it possible to uniquify a collection of objects which are normally non-hashable.
unknownWordDistSimClass - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
What class to assign to words not found in the dist sim lexicon.
unlock() - Method in class edu.stanford.nlp.util.HashIndex
Unlocks the Index.
unlock() - Method in interface edu.stanford.nlp.util.Index
Unlocks the Index.
unmodifiableCounter(Counter<T>) - Static method in class edu.stanford.nlp.stats.Counters
Returns unmodifiable view of the counter.
unmodifiableView() - Method in class edu.stanford.nlp.util.HashIndex
Returns an unmodifiable view of the Index.
update(double[], double[], double[], double[], double) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
update(double[], double[], double, double, double, double) - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
updateLabels(int[]) - Method in class edu.stanford.nlp.classify.Dataset
 
use2W - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
use4Clique - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
USE_ACCURACY - Static variable in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
USE_LOGLIKELIHOOD - Static variable in class edu.stanford.nlp.stats.MultiClassAccuracyStats
 
useAbbr - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAbbr1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useABGENE - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useABSTR - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useABSTRFreq - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useABSTRFreqDict - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAccCase - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAcqPrior - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useACR - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAgreement - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAltGazFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAnnexing - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useANTE - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useASBCChar2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useASBCPre1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useASBCSuf1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useAuxPairs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useBacktracking() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
useBeginSent - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useBig5 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useBigramInTwoClique - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useBoundarySequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useChPos - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
use POS information (an "open" feature for Chinese segmentation)
useChunks - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useChunkySequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useClassFeature - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useCommonWordsFeature - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useConcord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useConjBreak - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useConjugateGradientAscent(boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the minimizer to CGMinimizer, with the passed verbose flag.
useConjugateGradientAscent() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the minimizer to CGMinimizer.
useCorefFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useCTBChar2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useCTBPre1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useCTBSuf1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDiagonalScaling() - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
useDiagonalScaling() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
useDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictASBC2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictCTB2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictHK2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictionaryConjunctions - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictionaryConjunctions3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictleng - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDictPK2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDisjShape - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDisjunctive - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDisjunctiveShapeInteraction - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useDistSim - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useEitherSideDisjunctive - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useEitherSideWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useEntityRule - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useEntityTypes - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useEntityTypeSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useExternal - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useExtraTaggySequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesC4gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesC5gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesC6gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesCpC4gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesCpC5gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFeaturesCpC6gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFilter - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFirstNgram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFirstWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFloat - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useFREQ - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGazettePhrases - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGazettes - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGazFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGenericFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGENIA - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useGoodForNamesCpC - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHeadGov - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHk - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHKChar2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHKPre1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHKSuf1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHuber - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHybrid - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useHybridMinimizer() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useHybridMinimizer(double, int, StochasticCalculateMethods, int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useHybridMinimizerWithInPlaceSGD(int, int, double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useIfInteger - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useInna - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useInPlaceSGD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useInPlaceStochasticGradientDescent() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useInPlaceStochasticGradientDescent(int, int, double) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useInternal - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useIsDateRange - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useIsURL - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useIterable - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
useKBest - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLabelSource - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLastNgram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLastRealWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLC - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLemmaAsWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLemmas - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useLongSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMidDotShape - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMinimalAbbr - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMinimalAbbr1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMinPackSearch() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
useMoreAbbr - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMoreGazFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMoreTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMsr - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMSRChar2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useMUCFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegASBCDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegASBCDict3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegASBCDict4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegCTBDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegCTBDict3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegCTBDict4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegDict3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegDict4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegHKDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegHKDict3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegHKDict4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegPKDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegPKDict3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNegPKDict4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNeighborNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
Use prefixes and suffixes from the previous and next word.
useNERPrior - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNext - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNextRealWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNextSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNextVB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNGrams - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNoisyNonNoisyFeature - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNPGovernor - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNPHead - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useNumberFeature - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useObservedFeaturesOnly - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useObservedSequencesOnly - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useOccurrencePatterns - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useOnlySeenWeights - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useOrdinal - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useOutDict2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useParenMatching - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePath - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePhraseFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePhraseWords - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePhraseWordSpecialTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePhraseWordTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePk - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePKChar2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePKPre1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePKSuf1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePos - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePosition - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePPVBPairs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePre - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrediction - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrediction2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrev - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrevNextLemmas - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrevSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
usePrevVB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useProtoFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useQN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useQuartic - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useQuasiNewton() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
Sets the minimizer to QuasiNewton.
useQuasiNewton(boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useRad1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRad2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRad2b - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRadical - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useReverse - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useReverseAffix - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRobustQN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRule - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useRule2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useScalarScaling() - Method in class edu.stanford.nlp.optimization.QNMinimizer.QNInfo
 
useScalarScaling() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
useScaledSGD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSeenFeaturesOnly - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSegmentation - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSemPrior - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSentenceNumber - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSGD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSGDtoQN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeConjunctions - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeStrings - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeStrings1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeStrings3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeStrings4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useShapeStrings5 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSMD - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useStochasticGradientDescent() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticGradientDescent(double, int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticGradientDescentToQuasiNewton(double, int, int, int, int, int, boolean) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticMetaDescent() - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticMetaDescent(double, int, StochasticCalculateMethods, int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticQN(double, int) - Method in class edu.stanford.nlp.classify.LinearClassifierFactory
 
useStochasticQN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSuf - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSum - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSummedConditionalLikelihood - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
useSVO - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSymTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useSymWordPairs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
useSymWordPairs Has a small negative effect.
useTaggySequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTaggySequencesShapeInteraction - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTags - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTagsCpC - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTagsCpCp2C - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTagsCpCp2Cp3C - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTagsCpCp2Cp3Cp4C - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTemporalNN - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTitle - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTOK - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTopics - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTypeSeqs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTypeSeqs2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTypeSeqs3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useTypeySequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useUnicodeBlock - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useUnicodeType - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useUnicodeType4gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useUnicodeType5gram - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useUniformPrior - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
If true and doGibbs also true, will do generic Gibbs inference without any priors
useUnknown - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useURLSequences - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useVB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useViterbi - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWEB - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWEBFreqDict - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWideDisjunctive - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWord - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWord1 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWord2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWord3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWord4 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordLabelCounts - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordn - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordnetFeatures - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordPairs - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordShapeConjunctions2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordShapeConjunctions3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordShapeGaz - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordTag - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordUTypeConjunctions2 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useWordUTypeConjunctions3 - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useYear - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
useYetMoreCpCShapes - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 

V

v - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
value() - Method in class edu.stanford.nlp.ling.CoreLabel
Return a String representation of just the "main" value of this label.
value() - Method in interface edu.stanford.nlp.ling.Label
Return a String representation of just the "main" value of this label.
value() - Method in class edu.stanford.nlp.ling.StringLabel
Return the word value of the label (or null if none).
value() - Method in class edu.stanford.nlp.ling.ValueLabel
Return the value of the label (or null if none).
value() - Method in class edu.stanford.nlp.ling.WordLemmaTag
Return a String representation of just the "main" value of this Label.
value() - Method in class edu.stanford.nlp.ling.WordTag
Return a String representation of just the "main" value of this label.
value - Variable in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
valueAt(double[], double, int[]) - Method in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
valueAt(double[]) - Method in class edu.stanford.nlp.optimization.AbstractCachingDiffFunction
 
valueAt(double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
valueAt(x,batchSize) derivativeAt(x,batchSize) invokes the calculateStochastic function to get the current value at x for the next batchSize data points.
valueAt(double[], double[], int) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
This function will return the stochastic approximation at the point x.
valueAt(double[], double, int[]) - Method in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffUpdateFunction
Computes value of function for specified value of x (scaled by xcale) only over samples indexed by batch
valueAt(float[]) - Method in interface edu.stanford.nlp.optimization.FloatFunction
Returns the value of the function at a single point.
valueAt(double[]) - Method in interface edu.stanford.nlp.optimization.Function
Returns the value of the function at a single point.
ValueLabel - Class in edu.stanford.nlp.ling
A ValueLabel object acts as a Label with linguistic attributes.
ValueLabel() - Constructor for class edu.stanford.nlp.ling.ValueLabel
 
valueOf(String) - Static method in enum edu.stanford.nlp.classify.LogPrior.LogPriorType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.ling.AnnotationLookup.KeyLookup
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.ling.CoreAnnotations.SRL_ID
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in class edu.stanford.nlp.ling.WordTag
 
valueOf(String, String) - Static method in class edu.stanford.nlp.ling.WordTag
 
valueOf(String) - Static method in enum edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction.SamplingMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eLineSearch
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eScaling
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eState
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.optimization.StochasticCalculateMethods
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.util.Interval.RelType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.util.logging.Color
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.util.logging.Redwood.Flag
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum edu.stanford.nlp.util.logging.Style
Returns the enum constant of this type with the specified name.
valueOfIgnoreComments(String) - Static method in class edu.stanford.nlp.stats.ClassicCounter
Returns the Counter over Strings specified by this String.
values - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
values() - Static method in enum edu.stanford.nlp.classify.LogPrior.LogPriorType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.ling.AnnotationLookup.KeyLookup
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.ling.CoreAnnotations.SRL_ID
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction.SamplingMethod
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eLineSearch
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eScaling
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.optimization.QNMinimizer.eState
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.optimization.StochasticCalculateMethods
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Method in class edu.stanford.nlp.stats.ClassicCounter
Returns a copy of the values currently in this counter.
values() - Method in interface edu.stanford.nlp.stats.Counter
Returns a copy of the values currently in this counter.
values() - Method in class edu.stanford.nlp.stats.IntCounter
 
values() - Static method in enum edu.stanford.nlp.util.Interval.RelType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.util.logging.Color
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.util.logging.Redwood.Flag
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum edu.stanford.nlp.util.logging.Style
Returns an array containing the constants of this enum type, in the order they are declared.
valueSplit(String, String, String) - Static method in class edu.stanford.nlp.util.StringUtils
Split a string into tokens.
variance(double[]) - Static method in class edu.stanford.nlp.math.ArrayMath
 
verboseForTrueCasing - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
verboseMode - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
VisibilityHandler - Class in edu.stanford.nlp.util.logging
A filter for selecting which channels are visible.
VisibilityHandler() - Constructor for class edu.stanford.nlp.util.logging.VisibilityHandler
 

W

w - Variable in class edu.stanford.nlp.optimization.ScaledSGDMinimizer.weight
 
WARN - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
warn(Object...) - Static method in class edu.stanford.nlp.util.logging.Redwood.Util
 
WARN - Static variable in class edu.stanford.nlp.util.logging.Redwood
 
wasSuccessful() - Method in class edu.stanford.nlp.optimization.QNMinimizer
 
weakHashMapFactory() - Static method in class edu.stanford.nlp.util.MapFactory
Return a MapFactory that returns a WeakHashMap.
weight(F, L) - Method in class edu.stanford.nlp.classify.LinearClassifier
 
WeightedDataset<L,F> - Class in edu.stanford.nlp.classify
 
WeightedDataset(Index<L>, int[], Index<F>, int[][], int, float[]) - Constructor for class edu.stanford.nlp.classify.WeightedDataset
 
WeightedDataset() - Constructor for class edu.stanford.nlp.classify.WeightedDataset
 
WeightedDataset(int) - Constructor for class edu.stanford.nlp.classify.WeightedDataset
 
weights() - Method in class edu.stanford.nlp.classify.LinearClassifier
 
weights - Variable in class edu.stanford.nlp.classify.WeightedDataset
 
weightsAsCounter() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
weightsAsGenericCounter() - Method in class edu.stanford.nlp.classify.LogisticClassifier
 
weightsAsMapOfCounters() - Method in class edu.stanford.nlp.classify.LinearClassifier
This method returns a map from each label to a counter of feature weights for that label.
WHITE - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
wideDisjunctionWidth - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
wikiFeatureDbFile - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
word() - Method in class edu.stanford.nlp.ling.CoreLabel
Return the word value of the label (or null if none).
word() - Method in interface edu.stanford.nlp.ling.HasWord
Return the word value of the label (or null if none).
Word - Class in edu.stanford.nlp.ling
A Word object acts as a Label by containing a String.
Word() - Constructor for class edu.stanford.nlp.ling.Word
Construct a new word with a null value.
Word(String) - Constructor for class edu.stanford.nlp.ling.Word
Construct a new word, with the given value.
Word(String, int, int) - Constructor for class edu.stanford.nlp.ling.Word
Construct a new word, with the given value.
Word(Label) - Constructor for class edu.stanford.nlp.ling.Word
Creates a new word whose word value is the value of any class that supports the Label interface.
word() - Method in class edu.stanford.nlp.ling.Word
 
word() - Method in class edu.stanford.nlp.ling.WordLemmaTag
 
word() - Method in class edu.stanford.nlp.ling.WordTag
 
WordFactory - Class in edu.stanford.nlp.ling
A WordFactory acts as a factory for creating objects of class Word.
WordFactory() - Constructor for class edu.stanford.nlp.ling.WordFactory
Creates a new WordFactory.
wordFunction - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
This function maps words in the training or test data to new words.
WordLemmaTag - Class in edu.stanford.nlp.ling
A WordLemmaTag corresponds to a pair of a tagged (e.g., for part of speech) word and its lemma.
WordLemmaTag(String) - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
 
WordLemmaTag(Label) - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
 
WordLemmaTag() - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
 
WordLemmaTag(String, String) - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
Create a new WordLemmaTag.
WordLemmaTag(String, String, String) - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
Create a new WordLemmaTag.
WordLemmaTag(Label, Label) - Constructor for class edu.stanford.nlp.ling.WordLemmaTag
Create a new WordLemmaTag from a Label.
WordLemmaTagFactory - Class in edu.stanford.nlp.ling
/** A WordLemmaTagFactory acts as a factory for creating objects of class WordLemmaTag.
WordLemmaTagFactory() - Constructor for class edu.stanford.nlp.ling.WordLemmaTagFactory
Create a new WordLemmaTagFactory.
WordLemmaTagFactory(char) - Constructor for class edu.stanford.nlp.ling.WordLemmaTagFactory
Create a new WordLemmaTagFactory.
wordShape(String, int) - Static method in class edu.stanford.nlp.process.WordShapeClassifier
Specify the String and the int identifying which word shaper to use and this returns the result of using that wordshaper on the String.
wordShape(String, int, Collection<String>) - Static method in class edu.stanford.nlp.process.WordShapeClassifier
Specify the string and the int identifying which word shaper to use and this returns the result of using that wordshaper on the String.
wordShape - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
WORDSHAPECHRIS1 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPECHRIS2 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPECHRIS2USELC - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPECHRIS3 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPECHRIS3USELC - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPECHRIS4 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WordShapeClassifier - Class in edu.stanford.nlp.process
Provides static methods which map any String to another String indicative of its "word shape" -- e.g., whether capitalized, numeric, etc.
WORDSHAPEDAN1 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEDAN2 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEDAN2BIO - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEDAN2BIOUSELC - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEDAN2USELC - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEDIGITS - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
wordShapeGaz - Variable in class edu.stanford.nlp.sequences.SeqClassifierFlags
 
WORDSHAPEJENNY1 - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WORDSHAPEJENNY1USELC - Static variable in class edu.stanford.nlp.process.WordShapeClassifier
 
WordTag - Class in edu.stanford.nlp.ling
A WordTag corresponds to a tagged (e.g., for part of speech) word and is implemented with String-valued word and tag.
WordTag(String, String) - Constructor for class edu.stanford.nlp.ling.WordTag
Create a new WordTag.
WordTag(String) - Constructor for class edu.stanford.nlp.ling.WordTag
 
WordTag(E) - Constructor for class edu.stanford.nlp.ling.WordTag
 
WordTag() - Constructor for class edu.stanford.nlp.ling.WordTag
 
WordTag(Label, Label) - Constructor for class edu.stanford.nlp.ling.WordTag
Create a new WordTag from a Label.
WordTagFactory - Class in edu.stanford.nlp.ling
A WordTagFactory acts as a factory for creating objects of class WordTag.
WordTagFactory() - Constructor for class edu.stanford.nlp.ling.WordTagFactory
Create a new WordTagFactory.
WordTagFactory(char) - Constructor for class edu.stanford.nlp.ling.WordTagFactory
Create a new WordTagFactory.
WORKING - Static variable in class edu.stanford.nlp.classify.ClassifierExample
 
write(int) - Method in class edu.stanford.nlp.io.BZip2PipedOutputStream
 
write(byte[]) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
write(int) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
write(byte[], int, int) - Method in class edu.stanford.nlp.util.logging.RedwoodPrintStream
 
writeClassifier(LinearClassifier<?, ?>, String) - Static method in class edu.stanford.nlp.classify.LinearClassifier
Convenience wrapper for IOUtils.writeObjectToFile
writeObjectToFile(Object, String) - Static method in class edu.stanford.nlp.io.IOUtils
Write object to a file with the specified name.
writeObjectToFile(Object, File) - Static method in class edu.stanford.nlp.io.IOUtils
Write an object to a specified File.
writeObjectToFile(Object, File, boolean) - Static method in class edu.stanford.nlp.io.IOUtils
Write an object to a specified File.
writeObjectToFileNoExceptions(Object, String) - Static method in class edu.stanford.nlp.io.IOUtils
Write object to a file with the specified name.
writeObjectToTempFile(Object, String) - Static method in class edu.stanford.nlp.io.IOUtils
Write object to temp file which is destroyed when the program exits.
writeObjectToTempFileNoExceptions(Object, String) - Static method in class edu.stanford.nlp.io.IOUtils
Write object to a temp file and ignore exceptions.
writeStreamFromString(String) - Static method in class edu.stanford.nlp.io.IOUtils
 
writeStreamToStream(InputStream, OutputStream) - Static method in class edu.stanford.nlp.io.IOUtils
Send all bytes from the input stream to the output stream.
writeSVMLightFormat(File) - Method in class edu.stanford.nlp.classify.RVFDataset
Write the dataset in SVM-light format to the file.
writeSVMLightFormat(PrintWriter) - Method in class edu.stanford.nlp.classify.RVFDataset
 

X

x - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
x - Variable in class edu.stanford.nlp.optimization.StochasticMinimizer
 
xAD - Variable in class edu.stanford.nlp.classify.LogConditionalObjectiveFunction
 
xnorm - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 
xPerturbed - Variable in class edu.stanford.nlp.optimization.AbstractStochasticCachingDiffFunction
 
xscale - Variable in class edu.stanford.nlp.optimization.StochasticInPlaceMinimizer
 

Y

YELLOW - Static variable in class edu.stanford.nlp.util.logging.Redwood.Util
 
yList - Variable in class edu.stanford.nlp.optimization.ScaledSGDMinimizer
 

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