Package de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Subspace outlier detection methods Methods that detect outliers in subspaces (projections) of the data set.

See: Description

Class Summary

Class	Description
AbstractAggarwalYuOutlier<V extends NumberVector>	Abstract base class for the sparse-grid-cell based outlier detection of Aggarwal and Yu.
AbstractAggarwalYuOutlier.Parameterizer	Parameterization class.
AggarwalYuEvolutionary<V extends NumberVector>	Evolutionary variant (EAFOD) of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
AggarwalYuEvolutionary.Individuum	Individuum for the evolutionary search.
AggarwalYuEvolutionary.Parameterizer<V extends NumberVector>	Parameterization class.
AggarwalYuNaive<V extends NumberVector>	BruteForce variant of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
AggarwalYuNaive.Parameterizer<V extends NumberVector>	Parameterization class.
OutRankS1	OutRank: ranking outliers in high dimensional data.
OutRankS1.Parameterizer	Parameterization class.
OUTRES	Adaptive outlierness for subspace outlier ranking (OUTRES).
OUTRES.KernelDensityEstimator	Kernel density estimation and utility class.
OUTRES.Parameterizer	Parameterization class.
SOD<V extends NumberVector>	Subspace Outlier Degree.
SOD.Parameterizer<V extends NumberVector>	Parameterization class.
SOD.SODModel	SOD Model class

Package de.lmu.ifi.dbs.elki.algorithm.outlier.subspace Description

Subspace outlier detection methods

Methods that detect outliers in subspaces (projections) of the data set.