Package elki.utilities.scaling.outlier

Class COPOutlierScaling

  • All Implemented Interfaces:
    OutlierScaling, elki.utilities.scaling.ScalingFunction
    @Reference(authors="Hans-Peter Kriegel, Peer Kr\u00f6ger, Erich Schubert, Arthur Zimek",title="Outlier Detection in Arbitrarily Oriented Subspaces",booktitle="Proc. IEEE Int. Conf. on Data Mining (ICDM 2012)",url="https://doi.org/10.1109/ICDM.2012.21",bibkey="DBLP:conf/icdm/KriegelKSZ12") @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 COPOutlierScaling
extends java.lang.Object
implements OutlierScaling
    CDF based outlier score scaling.

    Enhanced version of the scaling proposed in:

    Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
    Interpreting and Unifying Outlier Scores
    Proc. 11th SIAM International Conference on Data Mining (SDM 2011)

    See also:

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

    Since:
    0.6.0
    Author:
    Erich Schubert

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      static class  COPOutlierScaling.Par
      Parameterization class.

    • Field Summary

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

    • Constructor Summary

      Constructors 
      Constructor Description
      COPOutlierScaling​(double phi)
      Constructor.

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      double getMax()  
      double getMin()  
      double getScaled​(double value)  
      <A> void prepare​(A array, elki.utilities.datastructures.arraylike.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

      • phi

        private double phi
        Phi parameter.

      • dist

        private elki.math.statistics.distribution.Distribution dist
        Score distribution.

      • inverted

        private boolean inverted
        Inversion flag.

    • Constructor Detail

      • COPOutlierScaling

        public COPOutlierScaling​(double phi)
        Constructor.
        Parameters:
        phi - Phi parameter

    • Method Detail

      • getScaled

        public double getScaled​(double value)
        Specified by:
        getScaled in interface elki.utilities.scaling.ScalingFunction

      • getMin

        public double getMin()
        Specified by:
        getMin in interface elki.utilities.scaling.ScalingFunction

      • getMax

        public double getMax()
        Specified by:
        getMax in interface elki.utilities.scaling.ScalingFunction

      • prepare

        public void prepare​(OutlierResult or)
        Description copied from interface: OutlierScaling
        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 OutlierScaling
        Parameters:
        or - Outlier result to use

      • prepare

        public <A> void prepare​(A array,
                        elki.utilities.datastructures.arraylike.NumberArrayAdapter<?,​A> adapter)
        Description copied from interface: OutlierScaling
        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 OutlierScaling
        Parameters:
        array - Data to process
        adapter - Array adapter