Uses of Interface
adams.data.binning.algorithm.BinningAlgorithm
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Packages that use BinningAlgorithm Package Description adams.data.binning.algorithm adams.data.statistics adams.flow.transformer weka.classifiers -
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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.
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