Class MinusLogStandardDeviationScaling

  • All Implemented Interfaces:
    OutlierScaling, ScalingFunction

    @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 MinusLogStandardDeviationScaling
    extends StandardDeviationScaling
    Scaling 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
    • Constructor Detail

      • MinusLogStandardDeviationScaling

        public MinusLogStandardDeviationScaling​(double fixedmean,
                                                double lambda)
        Constructor.
        Parameters:
        fixedmean - Fixed mean
        lambda - Scaling factor lambda
    • Method Detail

      • 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
        Overrides:
        prepare in class StandardDeviationScaling
        Parameters:
        or - Outlier result to use