Uses of Class
de.jstacs.classifiers.ClassDimensionException

Packages that use ClassDimensionException

de.jstacs.classifiers	This package provides the framework for any classifier.
de.jstacs.classifiers.assessment	This package allows to assess classifiers. It contains the class ClassifierAssessment that is used as a super-class of all implemented methodologies of an assessment to assess classifiers.
de.jstacs.classifiers.trainSMBased	Provides the classes for Classifiers that are based on TrainableStatisticalModels.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

Uses of ClassDimensionException in de.jstacs.classifiers

Methods in de.jstacs.classifiers that throw ClassDimensionException

static AbstractClassifier	ClassifierFactory.createGenerativeClassifier(TrainableStatisticalModel... models) Creates a classifier that is based on at least two TrainableStatisticalModels.
void	AbstractScoreBasedClassifier.setClassWeights(boolean add, double... weights) Sets new class weights.

Uses of ClassDimensionException in de.jstacs.classifiers.assessment

Constructors in de.jstacs.classifiers.assessment that throw ClassDimensionException

ClassifierAssessment(AbstractClassifier... aCs)
Creates a new ClassifierAssessment from a set of AbstractClassifiers.

ClassifierAssessment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
This constructor allows to assess a collection of given AbstractClassifiers and, in addition, classifiers that will be constructed using the given TrainableStatisticalModels.

ClassifierAssessment(AbstractClassifier[] aCs, TrainableStatisticalModel[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
Creates a new ClassifierAssessment from an array of AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel s, which are combined to additional classifiers.

ClassifierAssessment(boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
Creates a new ClassifierAssessment from a set of TrainableStatisticalModels.

KFoldCrossValidation(AbstractClassifier... aCs)
Creates a new KFoldCrossValidation from a set of AbstractClassifiers.

KFoldCrossValidation(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given TrainableStatisticalModels by a KFoldCrossValidation .

KFoldCrossValidation(AbstractClassifier[] aCs, TrainableStatisticalModel[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
Creates a new KFoldCrossValidation from an array of AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel s, which are combined to additional classifiers.

KFoldCrossValidation(boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
Creates a new KFoldCrossValidation from a set of TrainableStatisticalModels.

RepeatedHoldOutExperiment(AbstractClassifier... aCs)
Creates a new RepeatedHoldOutExperiment from a set of AbstractClassifiers.

RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given TrainableStatisticalModels by a RepeatedHoldOutExperiment.

RepeatedHoldOutExperiment(AbstractClassifier[] aCs, TrainableStatisticalModel[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
Creates a new RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel s, which are combined to additional classifiers.

RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
Creates a new RepeatedHoldOutExperiment from a set of TrainableStatisticalModels.

RepeatedSubSamplingExperiment(AbstractClassifier... aCs)
Creates a new RepeatedSubSamplingExperiment from a set of AbstractClassifiers.

RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given TrainableStatisticalModels by a RepeatedSubSamplingExperiment.

RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, TrainableStatisticalModel[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
Creates a new RepeatedSubSamplingExperiment from an array of AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel s, which are combined to additional classifiers.

RepeatedSubSamplingExperiment(boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
Creates a new RepeatedSubSamplingExperiment from a set of TrainableStatisticalModels.

Sampled_RepeatedHoldOutExperiment(AbstractClassifier... aCs)
Creates a new Sampled_RepeatedHoldOutExperiment from a set of AbstractClassifiers.

Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
This constructor allows to assess a collection of given AbstractClassifiers and those constructed using the given TrainableStatisticalModels by a Sampled_RepeatedHoldOutExperiment.

Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, TrainableStatisticalModel[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)
Creates a new Sampled_RepeatedHoldOutExperiment from an array of AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel s, which are combined to additional classifiers.

Sampled_RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, TrainableStatisticalModel[]... aMs)
Creates a new Sampled_RepeatedHoldOutExperiment from a set of TrainableStatisticalModels.

Uses of ClassDimensionException in de.jstacs.classifiers.trainSMBased

Constructors in de.jstacs.classifiers.trainSMBased that throw ClassDimensionException

TrainSMBasedClassifier(boolean cloneModels, TrainableStatisticalModel... models)
This constructor creates a new instance with the given TrainableStatisticalModels and clones these if necessary.

TrainSMBasedClassifier(TrainableStatisticalModel... models)
The default constructor that creates a new instance with the given TrainableStatisticalModels.

Uses of ClassDimensionException in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

Constructors in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared that throw ClassDimensionException

SharedStructureClassifier(int length, StructureLearner.ModelType model, byte order, StructureLearner.LearningType method, FSDAGTrainSM... models)
Creates a new SharedStructureClassifier from given FSDAGTrainSMs.