Package de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise

Normalizations operating on columns / variates; where each column is treated independently.

See: Description

Class Summary

Class	Description
AttributeWiseBetaNormalization<V extends NumberVector>	Project the data using a Beta distribution.
AttributeWiseBetaNormalization.Adapter	Array adapter class for vectors.
AttributeWiseBetaNormalization.Parameterizer<V extends NumberVector>	Parameterization class.
AttributeWiseCDFNormalization<V extends NumberVector>	Class to perform and undo a normalization on real vectors by estimating the distribution of values along each dimension independently, then rescaling objects to the cumulative density function (CDF) value at the original coordinate.
AttributeWiseCDFNormalization.Adapter	Array adapter class for vectors.
AttributeWiseCDFNormalization.Parameterizer<V extends NumberVector>	Parameterization class.
AttributeWiseErfNormalization<V extends NumberVector>	Attribute-wise Normalization using the error function.
AttributeWiseMADNormalization<V extends NumberVector>	Median Absolute Deviation is used for scaling the data set as follows: First, the median, and median absolute deviation are computed in each axis.
AttributeWiseMeanNormalization<V extends NumberVector>	Normalization designed for data with a meaningful zero: Each attribute is scaled to have the same mean (but 0 is not changed).
AttributeWiseMinMaxNormalization<V extends NumberVector>	Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector>	Parameterization class.
AttributeWiseVarianceNormalization<V extends NumberVector>	Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.
AttributeWiseVarianceNormalization.Parameterizer<V extends NumberVector>	Parameterization class.
IntegerRankTieNormalization	Normalize vectors according to their rank in the attributes.
IntegerRankTieNormalization.Sorter	Class to sort an index array by a particular dimension.
InverseDocumentFrequencyNormalization<V extends SparseNumberVector>	Normalization for text frequency (TF) vectors, using the inverse document frequency (IDF).

Package de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise Description

Normalizations operating on columns / variates; where each column is treated independently.