Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces.
|
Modifier and Type | Field and Description |
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protected AbstractDimensionsSelectingDoubleDistanceFunction<V> |
SUBCLU.Parameterizer.distance |
private AbstractDimensionsSelectingDoubleDistanceFunction<V> |
SUBCLU.distanceFunction
Holds the instance of the distance function specified by
SUBCLU.DISTANCE_FUNCTION_ID . |
Constructor and Description |
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SUBCLU(AbstractDimensionsSelectingDoubleDistanceFunction<V> distanceFunction,
DoubleDistance epsilon,
int minpts)
Constructor.
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Modifier and Type | Class and Description |
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class |
SubspaceEuclideanDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|
class |
SubspaceLPNormDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|
class |
SubspaceManhattanDistanceFunction
Provides a distance function that computes the Euclidean distance between
feature vectors only in specified dimensions.
|