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

Class COP<V extends NumberVector<?>,D extends NumberDistance<D,?>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<V,D,OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.COP<V,D>

Type Parameters:

V - the type of NumberVector handled by this Algorithm

D - Distance type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm, InspectionUtilFrequentlyScanned, Parameterizable

@Title(value="COP: Correlation Outlier Probability")
@Reference(authors="Hans-Peter Kriegel, Peer Kr\u00f6ger, Erich Schubert, Arthur Zimek",
           title="Outlier Detection in Arbitrarily Oriented Subspaces",
           booktitle="Proc. IEEE International Conference on Data Mining (ICDM 2012)")
public class COP<V extends NumberVector<?>,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<V,D,OutlierResult>
implements OutlierAlgorithm

Correlation outlier probability: Outlier Detection in Arbitrarily Oriented Subspaces

Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Outlier Detection in Arbitrarily Oriented Subspaces
in: Proc. IEEE International Conference on Data Mining (ICDM 2012)

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	COP.DistanceDist Score type.
static class	COP.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static String	COP_DIM Result name for the dimensionality.
static String	COP_ERRORVEC Result name for the error vectors.
static String	COP_SCORES Result name for the COP outlier scores.
(package private) COP.DistanceDist	dist Type of distribution to assume for distances.
(package private) double	expect Expected amount of outliers.
(package private) int	k Number of neighbors to be considered.
private static Logging	LOG The logger for this class.
private PCARunner<V>	pca Holds the PCA runner.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
COP(DistanceFunction<? super V,D> distanceFunction, int k, PCARunner<V> pca, double expect, COP.DistanceDist dist) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
OutlierResult	run(Relation<V> relation) Process a single relation.

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

getDistanceFunction

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

makeParameterDistanceFunction, 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.

COP_SCORES

public static final String COP_SCORES

Result name for the COP outlier scores.

See Also:

Constant Field Values

COP_DIM

public static final String COP_DIM

Result name for the dimensionality.

See Also:

Constant Field Values

COP_ERRORVEC

public static final String COP_ERRORVEC

Result name for the error vectors.

See Also:

Constant Field Values

k

int k

Number of neighbors to be considered.

pca

private PCARunner<V extends NumberVector<?>> pca

Holds the PCA runner.

expect

double expect

Expected amount of outliers.

dist

COP.DistanceDist dist

Type of distribution to assume for distances.

Constructor Detail

COP

public COP(DistanceFunction<? super V,D> distanceFunction,
   int k,
   PCARunner<V> pca,
   double expect,
   COP.DistanceDist dist)

Constructor.

Parameters:

distanceFunction - distance function

k - number of neighbors

pca - PCA computation method

expect - Expected fraction of outliers (for score normalization)

dist - Distance distribution model (ChiSquared, Gamma)

Method Detail

run

public OutlierResult run(Relation<V> relation)

Process a single relation.

Parameters:

relation - Relation to process

Returns:

Outlier detection result

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

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

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<OutlierResult>

Returns:

Type restriction

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