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

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

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.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.preprocessing	Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures.

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

DiSHDistanceFunction
Distance function used in the DiSH algorithm.

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

DimensionsSelectingEuclideanDistanceFunction
Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.

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

AbstractDimensionsSelectingDoubleDistanceFunction
Provides a distance function that computes the distance (which is a double distance) between feature vectors only in specified dimensions.

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

DimensionSelectingDistanceFunction
Provides a distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension.