de.lmu.ifi.dbs.elki.utilities.scaling.outlier

Class COPOutlierScaling

java.lang.Object

de.lmu.ifi.dbs.elki.utilities.scaling.outlier.COPOutlierScaling

All Implemented Interfaces:

Parameterizable, OutlierScalingFunction, ScalingFunction

@Reference(authors="H.-P. Kriegel, P. Kr\u00f6ger, E. Schubert, A. Zimek",
           title="Interpreting and Unifying Outlier Scores",
           booktitle="Proc. 11th SIAM International Conference on Data Mining (SDM), Mesa, AZ, 2011",
           url="http://siam.omnibooksonline.com/2011datamining/data/papers/018.pdf")
public class COPOutlierScaling
extends Object
implements OutlierScalingFunction

CDF based outlier score scaling. Enhanced version of the scaling proposed in:

H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
Interpreting and Unifying Outlier Scores
Proc. 11th SIAM International Conference on Data Mining (SDM), Mesa, AZ, 2011

See also:

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	COPOutlierScaling.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private Distribution	dist Score distribution.
private boolean	inverted Inversion flag.
private double	phi Phi parameter.

Constructor Summary

Constructors

Constructor and Description
COPOutlierScaling(double phi) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
double	getMax() Get maximum resulting value.
double	getMin() Get minimum resulting value.
double	getScaled(double value) Transform a given value using the scaling function.
<A> void	prepare(A array, NumberArrayAdapter<?,A> adapter) Prepare is called once for each data set, before getScaled() will be called.
void	prepare(OutlierResult or) Prepare is called once for each data set, before getScaled() will be called.
static void	secondReference() Secondary reference.

Methods inherited from class java.lang.Object

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

Field Detail

phi

private double phi

Phi parameter.

dist

private Distribution dist

Score distribution.

inverted

private boolean inverted

Inversion flag.

Constructor Detail

COPOutlierScaling

public COPOutlierScaling(double phi)

Constructor.

Parameters:

phi - Phi parameter

Method Detail

secondReference

@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 static final void secondReference()

Secondary reference.

getScaled

public double getScaled(double value)

Description copied from interface: ScalingFunction

Transform a given value using the scaling function.

Specified by:

getScaled in interface ScalingFunction

Parameters:

value - Original value

Returns:

Scaled value

getMin

public double getMin()

Description copied from interface: ScalingFunction

Get minimum resulting value. May be Double.NaN or Double.NEGATIVE_INFINITY.

Specified by:

getMin in interface ScalingFunction

Returns:

Minimum resulting value.

getMax

public double getMax()

Description copied from interface: ScalingFunction

Get maximum resulting value. May be Double.NaN or Double.POSITIVE_INFINITY.

Specified by:

getMax in interface ScalingFunction

Returns:

Maximum resulting value.

prepare

public void prepare(OutlierResult or)

Description copied from interface: OutlierScalingFunction

Prepare is called once for each data set, before getScaled() will be called. This function can be used to extract global parameters such as means, minimums or maximums from the outlier scores.

Specified by:

prepare in interface OutlierScalingFunction

Parameters:

or - Outlier result to use

prepare

public <A> void prepare(A array,
               NumberArrayAdapter<?,A> adapter)

Description copied from interface: OutlierScalingFunction

Prepare is called once for each data set, before getScaled() will be called. This function can be used to extract global parameters such as means, minimums or maximums from the score array. The method using a full OutlierResult is preferred, as it will allow access to the metadata.

Specified by:

prepare in interface OutlierScalingFunction

Parameters:

array - Data to process

adapter - Array adapter