Package | Description |
---|---|
de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise |
Normalizations operating on columns / variates; where each column is treated independently.
|
de.lmu.ifi.dbs.elki.datasource.filter.transform |
Data space transformations.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractNormalization<V extends NumberVector>
Abstract super class for all normalizations.
|
Modifier and Type | Class and Description |
---|---|
class |
AttributeWiseErfNormalization<V extends NumberVector>
Attribute-wise Normalization using the error function.
|
class |
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).
|
class |
AttributeWiseMinMaxNormalization<V extends NumberVector>
Class to perform and undo a normalization on real vectors with respect to
given minimum and maximum in each dimension.
|
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.
|
class |
InverseDocumentFrequencyNormalization<V extends SparseNumberVector>
Normalization for text frequency (TF) vectors, using the inverse document
frequency (IDF).
|
Modifier and Type | Class and Description |
---|---|
class |
GlobalPrincipalComponentAnalysisTransform<O extends NumberVector>
Apply principal component analysis to the data set.
|
class |
PerturbationFilter<V extends NumberVector>
A filter to perturb the values by adding micro-noise.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.