Uses of Class
de.jstacs.classifiers.performanceMeasures.NumericalPerformanceMeasureParameterSet

Packages that use NumericalPerformanceMeasureParameterSet

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.performanceMeasures	This package provides the implementations of performance measures that can be used to assess any classifier.

Uses of NumericalPerformanceMeasureParameterSet in de.jstacs.classifiers.assessment

Methods in de.jstacs.classifiers.assessment with parameters of type NumericalPerformanceMeasureParameterSet

ListResult	ClassifierAssessment.assess(NumericalPerformanceMeasureParameterSet mp, T assessPS, DataSet... s) Assesses the contained classifiers.
ListResult	ClassifierAssessment.assess(NumericalPerformanceMeasureParameterSet mp, T assessPS, ProgressUpdater pU, DataSet[] s) Assesses the contained classifiers.
ListResult	ClassifierAssessment.assess(NumericalPerformanceMeasureParameterSet mp, T assessPS, ProgressUpdater pU, DataSet[][]... s) Assesses the contained classifiers.
ListResult	ClassifierAssessment.assess(NumericalPerformanceMeasureParameterSet mp, T assessPS, ProgressUpdater pU, DataSet[] s, double[][] weights) Assesses the contained classifiers.
ListResult	KFoldCrossValidation.assessWithPredefinedSplits(NumericalPerformanceMeasureParameterSet mp, ClassifierAssessmentAssessParameterSet caaps, ProgressUpdater pU, DataSet[][] splitData, double[][][] splitWeights) This method implements a k-fold crossvalidation on previously split data.
protected void	KFoldCrossValidation.evaluateClassifier(NumericalPerformanceMeasureParameterSet mp, KFoldCrossValidationAssessParameterSet assessPS, DataSet[] s, double[][] weights, ProgressUpdater pU) Evaluates a classifier.
protected void	RepeatedHoldOutExperiment.evaluateClassifier(NumericalPerformanceMeasureParameterSet mp, RepeatedHoldOutAssessParameterSet assessPS, DataSet[] s, double[][] weights, ProgressUpdater pU) Evaluates the classifier.
protected void	RepeatedSubSamplingExperiment.evaluateClassifier(NumericalPerformanceMeasureParameterSet mp, RepeatedSubSamplingAssessParameterSet assessPS, DataSet[] s, double[][] weights, ProgressUpdater pU) Evaluates the classifier.
protected void	Sampled_RepeatedHoldOutExperiment.evaluateClassifier(NumericalPerformanceMeasureParameterSet mp, Sampled_RepeatedHoldOutAssessParameterSet assessPS, DataSet[] s, double[][] weights, ProgressUpdater pU)
protected abstract void	ClassifierAssessment.evaluateClassifier(NumericalPerformanceMeasureParameterSet mp, T assessPS, DataSet[] s, double[][] weights, ProgressUpdater pU) This method must be implemented in all subclasses.
protected void	ClassifierAssessment.test(NumericalPerformanceMeasureParameterSet mp, boolean exception, DataSet[] testS, double[][] weights) Uses the given test data sets to call the evaluate( ...

Uses of NumericalPerformanceMeasureParameterSet in de.jstacs.classifiers.performanceMeasures

Methods in de.jstacs.classifiers.performanceMeasures that return NumericalPerformanceMeasureParameterSet

static NumericalPerformanceMeasureParameterSet

AbstractPerformanceMeasureParameterSet.createFilledParameters() Creates a filled NumericalPerformanceMeasureParameterSet that can be used in AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...) or in a ClassifierAssessment.