Uses of Interface
adams.data.binning.algorithm.BinningAlgorithm

Packages that use BinningAlgorithm

Package	Description
adams.data.binning.algorithm
adams.data.statistics
adams.flow.transformer
weka.classifiers

Uses of BinningAlgorithm in adams.data.binning.algorithm

Subinterfaces of BinningAlgorithm in adams.data.binning.algorithm

Modifier and Type	Interface	Description
interface	FixedBinWidthBinningAlgorithm	Interface for binning algorithms that require a fixed bin width.
interface	FixedNumBinsBinningAlgorithm	Interface for binning algorithms that require to specify the number of bins.

Classes in adams.data.binning.algorithm that implement BinningAlgorithm

Modifier and Type	Class	Description
class	AbstractBinningAlgorithm	Ancestor for binning algorithms.
class	AbstractEqualWidthBinningAlgorithm	Ancestor for algorithms that use bins with the same width.
class	DensityBinning	Performs density-based binning.
class	FreedmanDiaconisChoiceBinning	The Freedman-Diaconis' choice is based on the interquartile range.
class	FrequencyBinning	Performs frequency binning.
class	ManualBinning	Generates a predefined number of equal sized bins.
class	NoBinning	Performs no real binning, just places all items in one bin.
class	RiceRuleBinning	The Rice Rule is presented as a simple alternative to Sturges's rule.
class	ScottsNormalReferenceRuleBinning	Scott's normal reference rule is optimal for random samples of normally distributed data, in the sense that it minimizes the integrated mean squared error of the density estimate.
class	SquareRootChoiceBinning	Takes the square root of the number of data points in the sample used by Excel histograms and many others) and rounds to the next integer.
class	SturgesFormulaBinning	Sturges' formula is derived from a binomial distribution and implicitly assumes an approximately normal distribution.

Methods in adams.data.binning.algorithm that return BinningAlgorithm

Modifier and Type	Method	Description
BinningAlgorithm	BinningAlgorithmUser.getAlgorithm()	Returns the binning algorithm.

Methods in adams.data.binning.algorithm with parameters of type BinningAlgorithm

Modifier and Type	Method	Description
void	BinningAlgorithmUser.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.

Uses of BinningAlgorithm in adams.data.statistics

Fields in adams.data.statistics declared as BinningAlgorithm

Modifier and Type	Field	Description
protected BinningAlgorithm	ArrayBinning.m_Algorithm	the binning algorithm.

Methods in adams.data.statistics that return BinningAlgorithm

Modifier and Type	Method	Description
BinningAlgorithm	ArrayBinning.getAlgorithm()	Returns the binning algorithm.

Methods in adams.data.statistics with parameters of type BinningAlgorithm

Modifier and Type	Method	Description
void	ArrayBinning.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.

Uses of BinningAlgorithm in adams.flow.transformer

Fields in adams.flow.transformer declared as BinningAlgorithm

Modifier and Type	Field	Description
protected BinningAlgorithm	SpreadSheetRowBinning.m_Algorithm	the binning algorithm to use.

Methods in adams.flow.transformer that return BinningAlgorithm

Modifier and Type	Method	Description
BinningAlgorithm	SpreadSheetRowBinning.getAlgorithm()	Returns the binning algorithm to use.

Methods in adams.flow.transformer with parameters of type BinningAlgorithm

Modifier and Type	Method	Description
void	SpreadSheetRowBinning.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm to use.

Uses of BinningAlgorithm in weka.classifiers

Fields in weka.classifiers declared as BinningAlgorithm

Modifier and Type	Field	Description
protected BinningAlgorithm	BinnedNumericClassCrossValidationFoldGenerator.m_Algorithm	the binning algorithm.
protected BinningAlgorithm	BinnedNumericClassRandomSplitGenerator.m_Algorithm	the binning algorithm.
protected BinningAlgorithm	GroupedBinnedNumericClassCrossValidationFoldGenerator.m_Algorithm	the binning algorithm.
protected BinningAlgorithm	GroupedBinnedNumericClassRandomSplitGenerator.m_Algorithm	the binning algorithm.
protected BinningAlgorithm[]	BestBinnedNumericClassRandomSplitGenerator.m_Algorithms	the algorithms to evaluate.

Methods in weka.classifiers that return BinningAlgorithm

Modifier and Type	Method	Description
BinningAlgorithm	BinnedNumericClassCrossValidationFoldGenerator.getAlgorithm()	Returns the binning algorithm.
BinningAlgorithm	BinnedNumericClassRandomSplitGenerator.getAlgorithm()	Returns the binning algorithm.
BinningAlgorithm	GroupedBinnedNumericClassCrossValidationFoldGenerator.getAlgorithm()	Returns the binning algorithm.
BinningAlgorithm	GroupedBinnedNumericClassRandomSplitGenerator.getAlgorithm()	Returns the binning algorithm.
BinningAlgorithm[]	BestBinnedNumericClassRandomSplitGenerator.getAlgorithms()	Returns the binning algorithms to choose from.

Methods in weka.classifiers with parameters of type BinningAlgorithm

Modifier and Type	Method	Description
void	BinnedNumericClassCrossValidationFoldGenerator.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.
void	BinnedNumericClassRandomSplitGenerator.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.
void	GroupedBinnedNumericClassCrossValidationFoldGenerator.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.
void	GroupedBinnedNumericClassRandomSplitGenerator.setAlgorithm(BinningAlgorithm value)	Sets the binning algorithm.
void	BestBinnedNumericClassRandomSplitGenerator.setAlgorithms(BinningAlgorithm[] value)	Sets the binning algorithms to choose from.

Constructors in weka.classifiers with parameters of type BinningAlgorithm

Constructor	Description
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm[] algorithms, double percentage)	Initializes the generator.
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm[] algorithms, long seed, double percentage)	Initializes the generator.
BestBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm[] algorithms, long seed, double percentage, boolean preserveOrder)	Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean stratify)	Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean randomize, boolean stratify, String relName)	Initializes the generator.
BinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, double percentage)	Initializes the generator.
BinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, long seed, double percentage)	Initializes the generator.
BinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, long seed, double percentage, boolean preserveOrder)	Initializes the generator.
GroupedBinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean randomize, boolean stratify, BaseRegExp regExp, String group, String relName)	Initializes the generator.
GroupedBinnedNumericClassCrossValidationFoldGenerator(weka.core.Instances data, BinningAlgorithm algorithm, int numFolds, long seed, boolean stratify, BaseRegExp regExp, String group)	Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, double percentage, BaseRegExp regExp, String group)	Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, long seed, double percentage, boolean preserveOrder, BaseRegExp regExp, String group)	Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(weka.core.Instances data, BinningAlgorithm algorithm, long seed, double percentage, BaseRegExp regExp, String group)	Initializes the generator.