Uses of Interface
org.neuroph.util.data.norm.Normalizer

Packages that use Normalizer

Package	Description
org.neuroph.util.data.norm	Provides data normalization techniques.

Uses of Normalizer in org.neuroph.util.data.norm

Classes in org.neuroph.util.data.norm that implement Normalizer

Modifier and Type	Class and Description
class	DecimalScaleNormalizer Decimal scaling normalization method, which normalize data by moving decimal point in regard to max element in training set (by columns) Normalization is done according to formula: normalizedVector[i] = vector[i] / scaleFactor[i]
class	MaxMinNormalizer MaxMin normalization method, which normalize data in regard to min and max elements in training set (by columns) Normalization is done according to formula: normalizedVector[i] = (vector[i] - min[i]) / (max[i] - min[i]) This class works fine if max and min are both positive and we want to normalize to [0,1]
class	MaxNormalizer Max normalization method, which normalize data in regard to max element in training set (by columns) Normalization is done according to formula: normalizedVector[i] = vector[i] / abs(max[i])
class	RangeNormalizer Performs normalization of a data set inputs and outputs to specified range.
class	ZeroMeanNormalizer Normalizes data sets by shifting all values in such way that data set has mean of 0 and standard deviation 1.