Package elki.utilities.scaling.outlier
Class StandardDeviationScaling
- java.lang.Object
-
- elki.utilities.scaling.outlier.StandardDeviationScaling
-
- All Implemented Interfaces:
OutlierScaling,elki.utilities.scaling.ScalingFunction
- Direct Known Subclasses:
MinusLogStandardDeviationScaling
@Reference(authors="Hans-Peter Kriegel, Peer Kr\u00f6ger, Erich Schubert, Arthur Zimek", title="Interpreting and Unifying Outlier Scores", booktitle="Proc. 11th SIAM International Conference on Data Mining (SDM 2011)", url="https://doi.org/10.1137/1.9781611972818.2", bibkey="DBLP:conf/sdm/KriegelKSZ11") public class StandardDeviationScaling extends java.lang.Object implements OutlierScalingScaling that can map arbitrary values to a probability in the range of [0:1].Transformation is done using the formula \(\max\{0, \mathrm{erf}(\lambda \frac{x-\mu}{\sigma\sqrt{2}})\}\)
Where mean can be fixed to a given value, and stddev is then computed against this mean.
Reference:
Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Interpreting and Unifying Outlier Scores
Proc. 11th SIAM International Conference on Data Mining (SDM 2011)- Since:
- 0.3
- Author:
- Erich Schubert
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static classStandardDeviationScaling.ParParameterization class.
-
Field Summary
Fields Modifier and Type Field Description (package private) doublefactorScaling factor to use (usually: Lambda * Stddev * Sqrt(2))protected doublefixedmeanField storing the fixed mean to useprotected doublelambdaField storing the lambda value(package private) doublemeanMean to use
-
Constructor Summary
Constructors Constructor Description StandardDeviationScaling()Constructor.StandardDeviationScaling(double fixedmean, double lambda)Constructor.
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description doublegetMax()doublegetMin()doublegetScaled(double value)<A> voidprepare(A array, elki.utilities.datastructures.arraylike.NumberArrayAdapter<?,A> adapter)Prepare is called once for each data set, before getScaled() will be called.voidprepare(OutlierResult or)Prepare is called once for each data set, before getScaled() will be called.
-
-
-
Method Detail
-
getScaled
public double getScaled(double value)
- Specified by:
getScaledin interfaceelki.utilities.scaling.ScalingFunction
-
prepare
public void prepare(OutlierResult or)
Description copied from interface:OutlierScalingPrepare 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:
preparein interfaceOutlierScaling- Parameters:
or- Outlier result to use
-
prepare
public <A> void prepare(A array, elki.utilities.datastructures.arraylike.NumberArrayAdapter<?,A> adapter)Description copied from interface:OutlierScalingPrepare 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 fullOutlierResultis preferred, as it will allow access to the metadata.- Specified by:
preparein interfaceOutlierScaling- Parameters:
array- Data to processadapter- Array adapter
-
getMin
public double getMin()
- Specified by:
getMinin interfaceelki.utilities.scaling.ScalingFunction
-
getMax
public double getMax()
- Specified by:
getMaxin interfaceelki.utilities.scaling.ScalingFunction
-
-