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, DistanceBasedAlgorithm<V,D>, OutlierAlgorithm, 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.
(package private) boolean	models Include models in output.
private PCARunner<V>	pca Holds the PCA runner.
private static NumberArrayAdapter<Double,double[]>	SHORTENED_ARRAY A clone of DoubleArrayAdapter that only uses the first 85% of the array!

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

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, boolean models) 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

SHORTENED_ARRAY

private static final NumberArrayAdapter<Double,double[]> SHORTENED_ARRAY

A clone of DoubleArrayAdapter that only uses the first 85% of the array!

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.

models

boolean models

Include models in output.

Constructor Detail

COP

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

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)

models - Report models

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