ELKI

Algorithms

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash	Helper classes for the CASH algorithm.
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.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial	Trivial clustering algorithms: all in one, no clusters, label clusterings These methods are mostly useful for providing a reference result in evaluation.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted	Weighted Neighborhood definitions.
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial	Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)