Uses of Interface
se.hb.jcp.cp.IConformalClassifier

Packages that use IConformalClassifier

Package	Description
se.hb.jcp.cli
se.hb.jcp.cp

Uses of IConformalClassifier in se.hb.jcp.cli

Methods in se.hb.jcp.cli that return IConformalClassifier

Modifier and Type	Method	Description
static IConformalClassifier	CCTools.loadModel(java.lang.String filename)

Methods in se.hb.jcp.cli with parameters of type IConformalClassifier

Modifier and Type	Method	Description
static DataSet	DataSetTools.loadDataSet(java.lang.String filename, IConformalClassifier cc)
static void	CCTools.runTest(IConformalClassifier cc, DataSet testSet, java.lang.String jsonOutputFileName, java.lang.String pValuesOutputFileName, java.lang.String labelsOutputFileName, double significanceLevel, boolean debug)
static void	CCTools.saveModel(IConformalClassifier cc, java.lang.String filename)

Uses of IConformalClassifier in se.hb.jcp.cp

Classes in se.hb.jcp.cp that implement IConformalClassifier

Modifier and Type	Class	Description
class	ConformalMultiProbabilisticClassifier	Represents a multi-probabilistic conformal classifier with bivariate isotonic regression.
class	InductiveConformalClassifier	Represents an instance of a specific inductive conformal classification algorithm.
class	TransductiveConformalClassifier

Methods in se.hb.jcp.cp that return IConformalClassifier

Modifier and Type	Method	Description
IConformalClassifier	ConformalMultiProbabilisticClassifier.getConformalClassifier()	Returns the underlying conformal classifier.
IConformalClassifier	ConformalClassification.getSource()	Returns the conformal classifier that made this prediction.

Constructors in se.hb.jcp.cp with parameters of type IConformalClassifier

Constructor	Description
ConformalClassification(IConformalClassifier source, cern.colt.matrix.DoubleMatrix1D pValues)
ConformalMultiProbabilisticClassification(IConformalClassifier source, cern.colt.matrix.DoubleMatrix1D pValues, double lower, double upper)
ConformalMultiProbabilisticClassifier(IConformalClassifier classifier)	Creates a multi-probabilistic conformal classifier with bivariate isotonic regression using the supplied information.