Package | Description |
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de.jstacs.classifiers |
This package provides the framework for any classifier.
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de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s by
a unified generative-discriminative learning principle. |
de.jstacs.classifiers.differentiableSequenceScoreBased.msp |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s either
by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL). |
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
Provides the classes for
AbstractScoreBasedClassifier s that are based on
SamplingDifferentiableStatisticalModel s
and that sample parameters using the Metropolis-Hastings algorithm. |
Class and Description |
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LearningPrinciple
This enum can be used to obtain the weights for well-known optimization tasks.
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Class and Description |
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GenDisMixClassifier
This class implements a classifier the optimizes the following function
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GenDisMixClassifierParameterSet
This class contains the parameters for the
GenDisMixClassifier . |
LearningPrinciple
This enum can be used to obtain the weights for well-known optimization tasks.
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LogGenDisMixFunction
This class implements the the following function
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Class and Description |
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GenDisMixClassifier
This class implements a classifier the optimizes the following function
![]() |
GenDisMixClassifierParameterSet
This class contains the parameters for the
GenDisMixClassifier . |
Class and Description |
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GenDisMixClassifier
This class implements a classifier the optimizes the following function
![]() |
GenDisMixClassifierParameterSet
This class contains the parameters for the
GenDisMixClassifier . |
LearningPrinciple
This enum can be used to obtain the weights for well-known optimization tasks.
|