@Title(value="Feature Bagging for Outlier Detection") @Reference(title="Feature Bagging for Outlier Detection", authors="A. Lazarevic, V. Kumar", booktitle="Proc. of the 11th ACM SIGKDD international conference on Knowledge discovery in data mining", url="http://dx.doi.org/10.1145/1081870.1081891") public class FeatureBagging extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm
Since the proposed method is only sensible to run on multiple instances of the same algorithm (due to incompatible score ranges), we do not allow using arbitrary algorithms.
Reference:
A. Lazarevic, V. Kumar: Feature Bagging for Outlier Detection
In: Proc. of the 11th ACM SIGKDD international conference on Knowledge
discovery in data mining
Modifier and Type | Class and Description |
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static class |
FeatureBagging.Parameterizer
Parameterization class.
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Modifier and Type | Field and Description |
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protected boolean |
breadth
Cumulative sum or breadth first combinations.
|
private int |
k
The parameters k for LOF.
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private static Logging |
LOG
The logger for this class.
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protected int |
num
Number of instances to use.
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private RandomFactory |
rnd
Random number generator for subspace choice.
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Constructor and Description |
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FeatureBagging(int k,
int num,
boolean breadth,
RandomFactory rnd)
Constructor.
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Modifier and Type | Method and Description |
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TypeInformation[] |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
|
protected Logging |
getLogger()
Get the (STATIC) logger for this class.
|
private long[] |
randomSubspace(int alldim,
int mindim,
int maxdim,
Random rand)
Choose a random subspace.
|
OutlierResult |
run(Database database,
Relation<NumberVector> relation)
Run the algorithm on a data set.
|
makeParameterDistanceFunction, run
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
run
private static final Logging LOG
protected int num
protected boolean breadth
private RandomFactory rnd
private int k
public FeatureBagging(int k, int num, boolean breadth, RandomFactory rnd)
k
- k Parameter for LOFnum
- Number of subspaces to usebreadth
- Flag for breadth-first mergingrnd
- Random generatorpublic OutlierResult run(Database database, Relation<NumberVector> relation)
database
- Database contextrelation
- Relation to useprivate long[] randomSubspace(int alldim, int mindim, int maxdim, Random rand)
alldim
- Number of total dimensionsmindim
- Minimum number to choosemaxdim
- Maximum number to chooseprotected Logging getLogger()
AbstractAlgorithm
getLogger
in class AbstractAlgorithm<OutlierResult>
public TypeInformation[] getInputTypeRestriction()
AbstractAlgorithm
getInputTypeRestriction
in interface Algorithm
getInputTypeRestriction
in class AbstractAlgorithm<OutlierResult>
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.