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

Outlier detection algorithms

See: Description

Interface Summary

Interface	Description
OutlierAlgorithm	Generic super interface for outlier detection algorithms.

Class Summary

Class	Description
ABOD<V extends NumberVector<V,?>>	Angle-Based Outlier Detection Outlier detection using variance analysis on angles, especially for high dimensional data sets.
ABOD.Parameterizer<V extends NumberVector<V,?>>	Parameterization class.
AbstractAggarwalYuOutlier<V extends NumberVector<?,?>>	Abstract base class for the sparse-grid-cell based outlier detection of Aggarwal and Yu.
AbstractAggarwalYuOutlier.Parameterizer	Parameterization class.
AbstractDBOutlier<O,D extends Distance<D>>	Simple distance based outlier detection algorithms.
AbstractDBOutlier.Parameterizer<O,D extends Distance<D>>	Parameterization class.
AggarwalYuEvolutionary<V extends NumberVector<?,?>>	EAFOD provides the evolutionary outlier detection algorithm, an algorithm to detect outliers for high dimensional data.
AggarwalYuEvolutionary.Individuum	Individuum for the evolutionary search.
AggarwalYuEvolutionary.Parameterizer<V extends NumberVector<?,?>>	Parameterization class.
AggarwalYuNaive<V extends NumberVector<?,?>>	BruteForce provides a naive brute force algorithm in which all k-subsets of dimensions are examined and calculates the sparsity coefficient to find outliers.
AggarwalYuNaive.Parameterizer<V extends NumberVector<?,?>>	Parameterization class.
DBOutlierDetection<O,D extends Distance<D>>	Simple distanced based outlier detection algorithm.
DBOutlierDetection.Parameterizer<O,D extends Distance<D>>	Parameterization class.
DBOutlierScore<O,D extends Distance<D>>	Compute percentage of neighbors in the given neighborhood with size d.
DBOutlierScore.Parameterizer<O,D extends Distance<D>>	Parameterization class.
EMOutlier<V extends NumberVector<V,?>>	outlier detection algorithm using EM Clustering.
EMOutlier.Parameterizer<V extends NumberVector<V,?>>	Parameterization class.
GaussianModel<V extends NumberVector<V,?>>	Outlier have smallest GMOD_PROB: the outlier scores is the probability density of the assumed distribution.
GaussianModel.Parameterizer<V extends NumberVector<V,?>>	Parameterization class.
GaussianUniformMixture<V extends NumberVector<V,?>>	Outlier detection algorithm using a mixture model approach.
GaussianUniformMixture.Parameterizer<V extends NumberVector<V,?>>	Parameterization class.
INFLO<O,D extends NumberDistance<D,?>>	INFLO provides the Mining Algorithms (Two-way Search Method) for Influence Outliers using Symmetric Relationship Reference: Jin, W., Tung, A., Han, J., and Wang, W. 2006 Ranking outliers using symmetric neighborhood relationship In Proc.
INFLO.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
KNNOutlier<O,D extends NumberDistance<D,?>>	Outlier Detection based on the distance of an object to its k nearest neighbor.
KNNOutlier.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
KNNWeightOutlier<O,D extends NumberDistance<D,?>>	Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
KNNWeightOutlier.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
LDOF<O,D extends NumberDistance<D,?>>	Computes the LDOF (Local Distance-Based Outlier Factor) for all objects of a Database.
LDOF.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
LOCI<O,D extends NumberDistance<D,?>>	Fast Outlier Detection Using the "Local Correlation Integral".
LOCI.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
LOF<O,D extends NumberDistance<D,?>>	Algorithm to compute density-based local outlier factors in a database based on a specified parameter LOF.K_ID (-lof.k).
LOF.LOFResult<O,D extends NumberDistance<D,?>>	Encapsulates information like the neighborhood, the LRD and LOF values of the objects during a run of the LOF algorithm.
LOF.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
LoOP<O,D extends NumberDistance<D,?>>	LoOP: Local Outlier Probabilities Distance/density based algorithm similar to LOF to detect outliers, but with statistical methods to achieve better result stability.
LoOP.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
OnlineLOF<O,D extends NumberDistance<D,?>>	Incremental version of the LOF Algorithm, supports insertions and removals.
OnlineLOF.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
OPTICSOF<O,D extends NumberDistance<D,?>>	OPTICSOF provides the Optics-of algorithm, an algorithm to find Local Outliers in a database.
OPTICSOF.Parameterizer<O,D extends NumberDistance<D,?>>	Parameterization class.
ReferenceBasedOutlierDetection<V extends NumberVector<?,?>,D extends NumberDistance<D,?>>	provides the Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.
ReferenceBasedOutlierDetection.Parameterizer<V extends NumberVector<?,?>,D extends NumberDistance<D,?>>	Parameterization class.
SOD<V extends NumberVector<V,?>>
SOD.Parameterizer<V extends NumberVector<V,?>>	Parameterization class.
SOD.SODModel<O extends NumberVector<O,?>>
SOD.SODProxyScoreResult	Proxy class that converts a model result to an actual SOD score result.

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

Outlier detection algorithms

See Also:

de.lmu.ifi.dbs.elki.algorithm