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

Distance-based outlier detection algorithms, such as DBOutlier and kNN.

See: Description

Class Summary

Class	Description
AbstractDBOutlier<O>	Simple distance based outlier detection algorithms.
AbstractDBOutlier.Parameterizer<O>	Parameterization class.
DBOutlierDetection<O>	Simple distanced based outlier detection algorithm.
DBOutlierDetection.Parameterizer<O>	Parameterization class.
DBOutlierScore<O>	Compute percentage of neighbors in the given neighborhood with size d.
DBOutlierScore.Parameterizer<O>	Parameterization class.
HilOut<O extends NumberVector>	Fast Outlier Detection in High Dimensional Spaces Outlier Detection using Hilbert space filling curves Reference: F.
HilOut.HilFeature	Hilbert representation of a single object.
HilOut.Parameterizer<O extends NumberVector>	Parameterization class
KNNOutlier<O>	Outlier Detection based on the distance of an object to its k nearest neighbor.
KNNOutlier.Parameterizer<O>	Parameterization class.
KNNWeightOutlier<O>	Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
KNNWeightOutlier.Parameterizer<O>	Parameterization class.
LocalIsolationCoefficient<O>	The Local Isolation Coefficient is the sum of the kNN distance and the average distance to its k nearest neighbors.
LocalIsolationCoefficient.Parameterizer<O>	Parameterization class.
ODIN<O>	Outlier detection based on the in-degree of the kNN graph.
ODIN.Parameterizer<O>	Parameterization class.
ReferenceBasedOutlierDetection	Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.
ReferenceBasedOutlierDetection.Parameterizer	Parameterization class.

Enum Summary

Enum	Description
HilOut.ScoreType	Type of output: all scores (upper bounds) or top n only

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

Distance-based outlier detection algorithms, such as DBOutlier and kNN. For methods based on local density, see package de.lmu.ifi.dbs.elki.algorithm.outlier.lof instead.