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## Uses of Class
de.jstacs.classifier.ClassDimensionException

Packages that use ClassDimensionException
de.jstacs.classifier | This package provides the framework for any classifier.
de.jstacs.classifier.assessment | This package allows to assess classifiers.
de.jstacs.classifier.modelBased | Provides the classes for `Classifier`s that are based on `Model`s
de.jstacs.models.discrete.inhomogeneous.shared |

Uses of ClassDimensionException in de.jstacs.classifier

Methods in de.jstacs.classifier that throw ClassDimensionException
`void` | `AbstractScoreBasedClassifier.setClassWeights(boolean add, double... weights)` Sets new class weights.
`ConfusionMatrix` | `AbstractClassifier.test(Sample... testData)` This method computes the confusion matrix for a given array of test data.

Uses of ClassDimensionException in de.jstacs.classifier.assessment

Constructors in de.jstacs.classifier.assessment that throw ClassDimensionException
`ClassifierAssessment(AbstractClassifier... aCs)` Creates a new `ClassifierAssessment` from a set of `AbstractClassifier`s.
`ClassifierAssessment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)` This constructor allows to assess a collection of given `AbstractClassifier`s and, in addition, classifiers that will be constructed using the given `AbstractModel`s.
`ClassifierAssessment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)` Creates a new `ClassifierAssessment` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
`ClassifierAssessment(boolean buildClassifiersByCrossProduct, Model[]... aMs)` Creates a new `ClassifierAssessment` from a set of `Model`s.
`KFoldCrossValidation(AbstractClassifier... aCs)` Creates a new `KFoldCrossValidation` from a set of `AbstractClassifier`s.
`KFoldCrossValidation(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)` This constructor allows to assess a collection of given `AbstractClassifier`s and those constructed using the given `AbstractModel`s by a `KFoldCrossValidation` .
`KFoldCrossValidation(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)` Creates a new `KFoldCrossValidation` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
`KFoldCrossValidation(boolean buildClassifiersByCrossProduct, Model[]... aMs)` Creates a new `KFoldCrossValidation` from a set of `Model`s.
`RepeatedHoldOutExperiment(AbstractClassifier... aCs)` Creates a new `RepeatedHoldOutExperiment` from a set of `AbstractClassifier`s.
`RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)` This constructor allows to assess a collection of given `AbstractClassifier`s and those constructed using the given `AbstractModel`s by a `RepeatedHoldOutExperiment`.
`RepeatedHoldOutExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)` Creates a new `RepeatedHoldOutExperiment` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
`RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)` Creates a new `RepeatedHoldOutExperiment` from a set of `Model`s.
`RepeatedSubSamplingExperiment(AbstractClassifier... aCs)` Creates a new `RepeatedSubSamplingExperiment` from a set of `AbstractClassifier`s.
`RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)` This constructor allows to assess a collection of given `AbstractClassifier`s and those constructed using the given `AbstractModel`s by a `RepeatedSubSamplingExperiment`.
`RepeatedSubSamplingExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)` Creates a new `RepeatedSubSamplingExperiment` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
`RepeatedSubSamplingExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)` Creates a new `RepeatedSubSamplingExperiment` from a set of `Model`s.
`Sampled_RepeatedHoldOutExperiment(AbstractClassifier... aCs)` Creates a new `Sampled_RepeatedHoldOutExperiment` from a set of `AbstractClassifier`s.
`Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, boolean buildClassifiersByCrossProduct, Model[]... aMs)` This constructor allows to assess a collection of given `AbstractClassifier`s and those constructed using the given `AbstractModel`s by a `Sampled_RepeatedHoldOutExperiment`.
`Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs, Model[][] aMs, boolean buildClassifiersByCrossProduct, boolean checkAlphabetConsistencyAndLength)` Creates a new `Sampled_RepeatedHoldOutExperiment` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
`Sampled_RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct, Model[]... aMs)` Creates a new `Sampled_RepeatedHoldOutExperiment` from a set of `Model`s.

Uses of ClassDimensionException in de.jstacs.classifier.modelBased

Constructors in de.jstacs.classifier.modelBased that throw ClassDimensionException
`ModelBasedClassifier(boolean cloneModels, Model... models)` This constructor creates a new instance with the given `Model`s and clones these if necessary.
`ModelBasedClassifier(Model... models)` The default constructor that creates a new instance with the given `Model`s.

Uses of ClassDimensionException in de.jstacs.models.discrete.inhomogeneous.shared

Constructors in de.jstacs.models.discrete.inhomogeneous.shared that throw ClassDimensionException
`SharedStructureClassifier(int length, StructureLearner.ModelType model, byte order, StructureLearner.LearningType method, FSDAGModel... models)` Creates a new `SharedStructureClassifier` from given `FSDAGModel`s.

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