Package | Description |
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de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
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de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation |
Distance functions using correlations.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces.
|
Modifier and Type | Field and Description |
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private FilteredLocalPCABasedDistanceFunction<V,?,D> |
COPAC.partitionDistanceFunction
Holds the instance of the preprocessed distance function
COPAC.PARTITION_DISTANCE_ID . |
protected FilteredLocalPCABasedDistanceFunction<V,?,D> |
COPAC.Parameterizer.pdistI |
Constructor and Description |
---|
COPAC(FilteredLocalPCABasedDistanceFunction<V,?,D> partitionDistanceFunction,
Class<? extends ClusteringAlgorithm<Clustering<Model>>> partitionAlgorithm,
Collection<Pair<OptionID,Object>> partitionAlgorithmParameters)
Constructor.
|
Modifier and Type | Class and Description |
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class |
LocallyWeightedDistanceFunction<V extends NumberVector<?,?>>
Provides a locally weighted distance function.
|
Modifier and Type | Class and Description |
---|---|
class |
ERiCDistanceFunction
Provides a distance function for building the hierarchy in the ERiC
algorithm.
|
class |
PCABasedCorrelationDistanceFunction
Provides the correlation distance for real valued vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
LocalSubspaceDistanceFunction
Provides a distance function to determine a kind of correlation distance
between two points, which is a pair consisting of the distance between the
two subspaces spanned by the strong eigenvectors of the two points and the
affine distance between the two subspaces.
|