Package de.lmu.ifi.dbs.elki.application.greedyensemble

Greedy ensembles for outlier detection.

See: Description

Class Summary

Class	Description
ComputeKNNOutlierScores<O extends NumberVector>	Application that runs a series of kNN-based algorithms on a data set, for building an ensemble in a second step.
ComputeKNNOutlierScores.Parameterizer<O extends NumberVector>	Parameterization class.
EvaluatePrecomputedOutlierScores	Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute popular evaluation metrics for it.
EvaluatePrecomputedOutlierScores.Parameterizer	Parameterization class.
GreedyEnsembleExperiment	Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute a naive ensemble for it.
GreedyEnsembleExperiment.Parameterizer	Parameterization class.
VisualizePairwiseGainMatrix	Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute a matrix with the pairwise gains.
VisualizePairwiseGainMatrix.Parameterizer	Parameterization class.

Enum Summary

Enum	Description
GreedyEnsembleExperiment.Distance	Distance modes.

Package de.lmu.ifi.dbs.elki.application.greedyensemble Description

Greedy ensembles for outlier detection.

This package contains code used for the greedy ensemble experiment in

Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel
On Evaluation of Outlier Rankings and Outlier Scores
Proc. 12th SIAM Int. Conf. on Data Mining (SDM 2012)