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 |
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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> |
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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 |
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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 (SVMLightClassifier s). |
WeightedDataset<L,F> |
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