Package edu.stanford.nlp.classify

Interface Summary
Classifier<L,F> A simple interface for classifying and scoring data points, implemented by most of the classifiers in this package.
ClassifierCreator<L,F> Creates a classifier with given weights
ClassifierFactory<L,F,C extends Classifier<L,F>> A simple interface for training a Classifier from a Dataset of training examples.
ProbabilisticClassifier<L,F>  
ProbabilisticClassifierCreator<L,F> Creates a probablic classifier with given weights
RVFClassifier<L,F> A simple interface for classifying and scoring data points with real-valued features.
 

Class Summary
AbstractLinearClassifierFactory<L,F> Shared methods for training a LinearClassifier.
AdaptedGaussianPriorObjectiveFunction<L,F> Adapt the mean of the Gaussian Prior by shifting the mean to the previously trained weights
BiasedLogConditionalObjectiveFunction Maximizes the conditional likelihood with a given prior.
CrossValidator<L,F> This class is meant to simplify performing cross validation on classifiers for hyper-parameters.
CrossValidator.SavedState  
Dataset<L,F> 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.
GeneralDataset<L,F> The purpose of this interface is to unify Dataset and RVFDataset.
GeneralizedExpectationObjectiveFunction<L,F> Implementation of Generalized Expectation Objective function for an I.I.D.
LinearClassifier<L,F> Implements a multiclass linear classifier.
LinearClassifierFactory<L,F> Builds various types of linear classifiers, with functionality for setting objective function, optimization method, and other parameters.
LinearClassifierFactory.LinearClassifierCreator<L,F>  
LogConditionalObjectiveFunction<L,F> Maximizes the conditional likelihood with a given prior.
LogPrior A Prior for functions.
NBLinearClassifierFactory<L,F> Provides a medium-weight implementation of Bernoulli (or binary) Naive Bayes via a linear classifier.
PRCurve  
RVFDataset<L,F> 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.
SemiSupervisedLogConditionalObjectiveFunction Maximizes the conditional likelihood with a given prior.
SVMLightClassifier<L,F> This class represents a trained SVM Classifier.
SVMLightClassifierFactory<L,F> This class is meant for training SVMs (SVMLightClassifiers).
WeightedDataset<L,F>  
 

Enum Summary
LogPrior.LogPriorType  
 



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