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

Class AggarwalYuEvolutionary<V extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier<V>

de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary<V>

Type Parameters:

V - the type of FeatureVector handled by this Algorithm

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

@Title(value="EAFOD: the evolutionary outlier detection algorithm")
 @Description(value="Outlier detection for high dimensional data")
 @Reference(authors="C. C. Aggarwal, P. S. Yu",
           title="Outlier detection for high dimensional data",
           booktitle="Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD 2001)",
           url="https://doi.org/10.1145/375663.375668",
           bibkey="DBLP:conf/sigmod/AggarwalY01")
 @Alias(value="de.lmu.ifi.dbs.elki.algorithm.outlier.AggarwalYuEvolutionary")
public class AggarwalYuEvolutionary<V extends NumberVector>
extends AbstractAggarwalYuOutlier<V>

Evolutionary variant (EAFOD) of the high-dimensional outlier detection algorithm by Aggarwal and Yu.

Reference:

Outlier detection for high dimensional data
C. C. Aggarwal, P. S. Yu
Proc. 2001 ACM SIGMOD international conference on Management of data

Since:

0.4.0

Author:

Ahmed Hettab, Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
private class	AggarwalYuEvolutionary.EvolutionarySearch The inner class to handle the actual evolutionary computation.
private static class	AggarwalYuEvolutionary.Individuum Individuum for the evolutionary search.
static class	AggarwalYuEvolutionary.Parameterizer<V extends NumberVector> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
protected static double	CONVERGENCE At which gene homogenity do we have convergence?
private static Logging	LOG The logger for this class.
private int	m Holds the value of AggarwalYuEvolutionary.Parameterizer.M_ID.
protected static int	MAX_ITERATIONS Maximum iteration count for evolutionary search.
private RandomFactory	rnd Random generator.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier

DONT_CARE, GENE_OFFSET, k, phi

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
AggarwalYuEvolutionary(int k, int phi, int m, RandomFactory rnd) Constructor.

Method Summary

Modifier and Type	Method and Description
protected Logging	getLogger() Get the (STATIC) logger for this class.
OutlierResult	run(Database database, Relation<V> relation) Performs the evolutionary algorithm on the given database.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier

buildRanges, computeSubspace, computeSubspaceForGene, getInputTypeRestriction, sparsity

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.outlier.OutlierAlgorithm

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

MAX_ITERATIONS

protected static final int MAX_ITERATIONS

Maximum iteration count for evolutionary search.

See Also:

Constant Field Values

CONVERGENCE

protected static final double CONVERGENCE

At which gene homogenity do we have convergence?

See Also:

Constant Field Values

m

private int m

Holds the value of AggarwalYuEvolutionary.Parameterizer.M_ID.

rnd

private RandomFactory rnd

Random generator.

Constructor Detail

AggarwalYuEvolutionary

public AggarwalYuEvolutionary(int k,
                              int phi,
                              int m,
                              RandomFactory rnd)

Constructor.

Parameters:

k - K

phi - Phi

m - M

rnd - Random generator

Method Detail

run

public OutlierResult run(Database database,
                         Relation<V> relation)

Performs the evolutionary algorithm on the given database.

Parameters:

database - Database

relation - Relation

Returns:

Result

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<OutlierResult>

Returns:

the static logger