Package elki.outlier.subspace
Class OutRankS1
- java.lang.Object
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- elki.outlier.subspace.OutRankS1
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- 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
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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
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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.
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Constructor Summary
Constructors Constructor Description OutRankS1(SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg, double alpha)
Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description OutlierResult
autorun(Database database)
Try to auto-run the algorithm on a database by calling a method calledrun
, with an optionalDatabase
first, and with data relations as specified byAlgorithm.getInputTypeRestriction()
.TypeInformation[]
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
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Field Detail
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clusteralg
protected SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg
Clustering algorithm to run.
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alpha
double alpha
Weighting parameter of size vs. dimensionality score.
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Constructor Detail
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OutRankS1
public OutRankS1(SubspaceClusteringAlgorithm<? extends SubspaceModel> clusteralg, double alpha)
Constructor.- Parameters:
clusteralg
-SubspaceClusteringAlgorithm
to usealpha
- Alpha parameter to balance size and dimensionality.
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Method Detail
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getInputTypeRestriction
public TypeInformation[] getInputTypeRestriction()
Description copied from interface:Algorithm
Get the input type restriction used for negotiating the data query.- Specified by:
getInputTypeRestriction
in interfaceAlgorithm
- Returns:
- Type restriction
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autorun
public OutlierResult autorun(Database database)
Description copied from interface:Algorithm
Try to auto-run the algorithm on a database by calling a method calledrun
, with an optionalDatabase
first, and with data relations as specified byAlgorithm.getInputTypeRestriction()
.- Specified by:
autorun
in interfaceAlgorithm
- Specified by:
autorun
in interfaceOutlierAlgorithm
- Parameters:
database
- the database to run the algorithm on- Returns:
- the Result computed by this algorithm
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