Uses of Package
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Packages that use de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

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.

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace used by de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Class and Description
DimensionSelectingSubspaceDistanceFunction Interface for dimension selecting subspace distance functions.

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace used by de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Class and Description
AbstractDimensionsSelectingDistanceFunction Abstract base class for distances computed only in subspaces.
AbstractDimensionsSelectingDistanceFunction.Parameterizer Parameterization class.
DimensionSelectingSubspaceDistanceFunction Interface for dimension selecting subspace distance functions.
OnedimensionalDistanceFunction Distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension only.
SubspaceEuclideanDistanceFunction Euclidean distance function between NumberVectors only in specified dimensions.
SubspaceLPNormDistanceFunction LP-Norm distance function between NumberVectors only in specified dimensions.
SubspaceManhattanDistanceFunction Manhattan distance function between NumberVectors only in specified dimensions.
SubspaceMaximumDistanceFunction Maximum distance function between NumberVectors only in specified dimensions.