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

Class StandardDeviationScaling

java.lang.Object

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

All Implemented Interfaces:

Parameterizable, OutlierScalingFunction, ScalingFunction

Direct Known Subclasses:

MinusLogStandardDeviationScaling

@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 StandardDeviationScaling
extends Object
implements OutlierScalingFunction

Scaling that can map arbitrary values to a probability in the range of [0:1]. Transformation is done using the formula max(0, erf(lambda * (x - mean) / (stddev * sqrt(2)))) Where mean can be fixed to a given value, and stddev is then computed against this mean. Reference:

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

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	StandardDeviationScaling.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) double	factor Scaling factor to use (usually: Lambda * Stddev * Sqrt(2))
protected Double	fixedmean Field storing the fixed mean to use
protected double	lambda Field storing the lambda value
(package private) double	mean Mean to use

Constructor Summary

Constructors

Constructor and Description
StandardDeviationScaling() Constructor.
StandardDeviationScaling(Double fixedmean, double lambda) 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.

Methods inherited from class java.lang.Object

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

Field Detail

fixedmean

protected Double fixedmean

Field storing the fixed mean to use

lambda

protected double lambda

Field storing the lambda value

mean

double mean

Mean to use

factor

double factor

Scaling factor to use (usually: Lambda * Stddev * Sqrt(2))

Constructor Detail

StandardDeviationScaling

public StandardDeviationScaling(Double fixedmean,
                        double lambda)

Constructor.

Parameters:

fixedmean - Fixed mean

lambda - Scaling factor lambda

StandardDeviationScaling

public StandardDeviationScaling()

Constructor.

Method Detail

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

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

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.