Uses of Class
adams.data.binning.algorithm.AbstractBinningAlgorithm

Packages that use AbstractBinningAlgorithm

Package	Description
adams.data.binning.algorithm

Uses of AbstractBinningAlgorithm in adams.data.binning.algorithm

Subclasses of AbstractBinningAlgorithm in adams.data.binning.algorithm

Modifier and Type	Class	Description
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.