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## Uses of Package
de.jstacs.classifier

Packages that use de.jstacs.classifier
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.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
de.jstacs.classifier.scoringFunctionBased.gendismix | Provides an implementation of a classifier that allows to train the parameters of a set of `NormalizableScoringFunction`s by a unified generative-discriminative learning principle
de.jstacs.classifier.scoringFunctionBased.msp | Provides an implementation of a classifier that allows to train the parameters of a set of `ScoringFunctions` either by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL)
de.jstacs.classifier.utils | Provides some useful classes for working with classifiers
de.jstacs.models.discrete.inhomogeneous.shared |

Classes in de.jstacs.classifier used by de.jstacs.classifier
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.
AbstractScoreBasedClassifier.DoubleTableResult This class is for `Result`s given as a table of `double` s.
ClassDimensionException This class indicates that a classifier is defined for less than 2 classes or is defined over a different number of classes than given (e.g. by an array of `Sample`s).
ConfusionMatrix This class holds the confusion matrix of a classifier.
MeasureParameters This class holds the parameters for the `evaluate`-methods of a classifier.
MeasureParameters.Measure This `enum` defines all measures that are currently implemented in Jstacs.
ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair This class is used as a container that allows to store a threshold and the result of a measure together.

Classes in de.jstacs.classifier used by de.jstacs.classifier.assessment
AbstractClassifier The super class for any classifier.
ClassDimensionException This class indicates that a classifier is defined for less than 2 classes or is defined over a different number of classes than given (e.g. by an array of `Sample`s).
MeasureParameters This class holds the parameters for the `evaluate`-methods of a classifier.

Classes in de.jstacs.classifier used by de.jstacs.classifier.modelBased
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.
ClassDimensionException This class indicates that a classifier is defined for less than 2 classes or is defined over a different number of classes than given (e.g. by an array of `Sample`s).

Classes in de.jstacs.classifier used by de.jstacs.classifier.scoringFunctionBased
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.

Classes in de.jstacs.classifier used by de.jstacs.classifier.scoringFunctionBased.gendismix
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.

Classes in de.jstacs.classifier used by de.jstacs.classifier.scoringFunctionBased.msp
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.

Classes in de.jstacs.classifier used by de.jstacs.classifier.utils
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.

Classes in de.jstacs.classifier used by de.jstacs.models.discrete.inhomogeneous.shared
AbstractClassifier The super class for any classifier.
AbstractScoreBasedClassifier This class is the main class for all score based classifiers.
ClassDimensionException This class indicates that a classifier is defined for less than 2 classes or is defined over a different number of classes than given (e.g. by an array of `Sample`s).

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