Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.datasource.filter.normalization |
Data normalization.
|
Class and Description |
---|
NonNumericFeaturesException
An exception to signal the encounter of non numeric features where numeric
features have been expected.
|
Class and Description |
---|
NonNumericFeaturesException
An exception to signal the encounter of non numeric features where numeric
features have been expected.
|
Normalization
Normalization performs a normalization on a set of feature vectors and is
capable to transform a set of feature vectors to the original attribute
ranges.
|
Class and Description |
---|
AbstractNormalization
Abstract super class for all normalizations.
|
AbstractStreamNormalization
Abstract super class for all normalizations.
|
AttributeWiseMinMaxNormalization
Class to perform and undo a normalization on real vectors with respect to
given minimum and maximum in each dimension.
|
AttributeWiseVarianceNormalization
Class to perform and undo a normalization on real vectors with respect to
given mean and standard deviation in each dimension.
|
InverseDocumentFrequencyNormalization
Normalization for text frequency vectors, using the inverse document
frequency.
|
LengthNormalization
Class to perform a normalization on vectors to norm 1.
|
NonNumericFeaturesException
An exception to signal the encounter of non numeric features where numeric
features have been expected.
|
Normalization
Normalization performs a normalization on a set of feature vectors and is
capable to transform a set of feature vectors to the original attribute
ranges.
|