Package de.jstacs.classifiers.performanceMeasures

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

See:
          Description

Interface Summary
NumericalPerformanceMeasure This interface indicates that a Performance measure returns numerical results.
PerformanceMeasure Interface of any performance measure used to evaluate an AbstractClassifier.
 

Class Summary
AbstractNumericalTwoClassPerformanceMeasure This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
AbstractPerformanceMeasure This class is the abstract super class of any performance measure used to evaluate an AbstractClassifier.
AbstractPerformanceMeasureParameterSet<T extends PerformanceMeasure> This class implements a container of PerformanceMeasures that can be used in AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...).
AbstractTwoClassPerformanceMeasure This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
AucPR This class implements the area under curve of the precision-recall curve.
AucROC This class implements the area under curve of the Receiver Operating Characteristics curve.
ClassificationRate This class implements the classification rate, i.e.
ConfusionMatrix This class implements the performance measure confusion matrix.
FalsePositiveRateForFixedSensitivity This class implements the false positive rate for a fixed sensitivity.
MaximumCorrelationCoefficient This class implements the maximum of the correlation coefficient $\frac{ TP*TN - FN*FP }{ \sqrt{ (TP+FN)*(TN+FP)*(TP+FP)*(TN+FN) } }$.
MaximumFMeasure Computes the maximum of the general F-measure given a positive real parameter $\beta$.
MaximumNumericalTwoClassMeasure This class prepares everything for an easy implementation of a maximum of any numerical performance measure.
NumericalPerformanceMeasureParameterSet This class implements a container for NumericalPerformanceMeasures that can be used, for instance, in an repeated assessment, (cf.
PerformanceMeasureParameterSet This class implements a container of AbstractPerformanceMeasures that can be used in AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...).
PositivePredictiveValueForFixedSensitivity This class implements the positive predictive value for a fixed sensitivity.
PRCurve This class implements the precision-recall curve and its area under the curve.
ROCCurve This class implements the Receiver Operating Characteristics curve and the area under the curve.
SensitivityForFixedSpecificity This class implements the sensitivity for a fixed specificity.
 

Package de.jstacs.classifiers.performanceMeasures Description

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

See Also:
AbstractPerformanceMeasure, PerformanceMeasureParameterSet, AbstractClassifier