Package elki.outlier.subspace

Class OutRankS1

java.lang.Object

elki.outlier.subspace.OutRankS1

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

@Title("OutRank: ranking outliers in high dimensional data")
@Description("Ranking outliers in high dimensional data - score 1")
@Reference(authors="E. M\u00fcller, I. Assent, U. Steinhausen, T. Seidl",
           title="OutRank: ranking outliers in high dimensional data",
           booktitle="Proc. 24th Int. Conf. on Data Engineering (ICDE) Workshop on Ranking in Databases (DBRank)",
           url="https://doi.org/10.1109/ICDEW.2008.4498387",
           bibkey="DBLP:conf/icde/MullerASS08")
public class OutRankS1
extends java.lang.Object
implements OutlierAlgorithm

OutRank: ranking outliers in high dimensional data.

Algorithm to score outliers based on a subspace clustering result. This class implements score 1 of the OutRank publication, which is a score based on cluster sizes and cluster dimensionality.

Reference:

E. Müller, I. Assent, U. Steinhausen, T. Seidl
OutRank: ranking outliers in high dimensional data
In Proceedings 24th International Conference on Data Engineering (ICDE) Workshop on Ranking in Databases (DBRank)

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	OutRankS1.Par	Parameterization class.

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
(package private) double	alpha	Weighting parameter of size vs. dimensionality score.
protected SubspaceClusteringAlgorithm<? extends SubspaceModel>	clusteralg	Clustering algorithm to run.

Constructor Summary

Constructors

Constructor	Description
OutRankS1(SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg, double alpha)	Constructor.

Method Summary

Modifier and Type	Method	Description
OutlierResult	autorun(Database database)	Try to auto-run the algorithm on a database by calling a method called run, with an optional Database first, and with data relations as specified by Algorithm.getInputTypeRestriction().
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

clusteralg

protected SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg

Clustering algorithm to run.

alpha

double alpha

Weighting parameter of size vs. dimensionality score.

Constructor Detail

OutRankS1

public OutRankS1(SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg,
                 double alpha)

Constructor.

Parameters:

clusteralg - SubspaceClusteringAlgorithm to use

alpha - Alpha parameter to balance size and dimensionality.

Method Detail

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from interface: Algorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Returns:

Type restriction

autorun

public OutlierResult autorun(Database database)

Description copied from interface: Algorithm

Try to auto-run the algorithm on a database by calling a method called run, with an optional Database first, and with data relations as specified by Algorithm.getInputTypeRestriction().

Specified by:

autorun in interface Algorithm

Specified by:

autorun in interface OutlierAlgorithm

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm