Package elki.outlier.subspace

Class OUTRES

  • All Implemented Interfaces:
    elki.Algorithm, OutlierAlgorithm
    @Reference(authors="E. M\u00fcller, M. Schiffer, T. Seidl",
           title="Adaptive outlierness for subspace outlier ranking",
           booktitle="Proc. 19th ACM Int. Conf. on Information and Knowledge Management",
           url="https://doi.org/10.1145/1871437.1871690",
           bibkey="DBLP:conf/cikm/MullerSS10")
public class OUTRES
extends java.lang.Object
implements OutlierAlgorithm
    Adaptive outlierness for subspace outlier ranking (OUTRES).

    Note: this algorithm seems to have a O(n³d!) complexity with no obvious way to accelerate it with usual index structures for range queries: each object in each tested subspace will need to know the mean and standard deviation of the density of the neighbors, which in turn needs another range query; except if we precomputed the densities for each of O(d!) possible subsets of dimensions.

    Reference:

    E. Müller, M. Schiffer, T. Seidl
    Adaptive outlierness for subspace outlier ranking
    Proc. 19th ACM Int. Conf. on Information and Knowledge Management

    Since:
    0.5.0
    Author:
    Viktoria Pleintinger, Erich Schubert

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      protected static class  OUTRES.KernelDensityEstimator
      Kernel density estimation and utility class.
      static class  OUTRES.Par
      Parameterization class.

      • Nested classes/interfaces inherited from interface elki.Algorithm

        elki.Algorithm.Utils

    • Field Summary

      Fields 
      Modifier and Type Field Description
      private double eps
      The epsilon (in 2d) parameter
      private static double K_S_CRITICAL001
      Constant for Kolmogorov-Smirnov at alpha=0.01 (table value)
      private static elki.logging.Logging LOG
      The logger for this class.

    • Constructor Summary

      Constructors 
      Constructor Description
      OUTRES​(double eps)
      Constructor.

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      elki.data.type.TypeInformation[] getInputTypeRestriction()  
      private elki.database.ids.DoubleDBIDList initialRange​(elki.database.ids.DBIDRef obj, elki.database.ids.DBIDs cands, elki.distance.PrimitiveDistance<? super elki.data.NumberVector> df, double eps, OUTRES.KernelDensityEstimator kernel, elki.database.ids.ModifiableDoubleDBIDList n)
      Initial range query.
      double outresScore​(int s, long[] subspace, elki.database.ids.DBIDRef id, OUTRES.KernelDensityEstimator kernel, elki.database.ids.DBIDs cands)
      Main loop of OUTRES.
      protected boolean relevantSubspace​(long[] subspace, elki.database.ids.DoubleDBIDList neigh, OUTRES.KernelDensityEstimator kernel)
      Subspace relevance test.
      OutlierResult run​(elki.database.relation.Relation<? extends elki.data.NumberVector> relation)
      Main loop for OUTRES
      private elki.database.ids.DoubleDBIDList subsetNeighborhoodQuery​(elki.database.ids.DoubleDBIDList neighc, elki.database.ids.DBIDRef dbid, elki.distance.PrimitiveDistance<? super elki.data.NumberVector> df, double adjustedEps, OUTRES.KernelDensityEstimator kernel, elki.database.ids.ModifiableDoubleDBIDList n)
      Refine neighbors within a subset.

      • Methods inherited from class java.lang.Object

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

    • Field Detail

      • LOG

        private static final elki.logging.Logging LOG
        The logger for this class.

      • eps

        private final double eps
        The epsilon (in 2d) parameter

      • K_S_CRITICAL001

        private static final double K_S_CRITICAL001
        Constant for Kolmogorov-Smirnov at alpha=0.01 (table value)
        See Also:
        Constant Field Values

    • Constructor Detail

      • OUTRES

        public OUTRES​(double eps)
        Constructor.
        Parameters:
        eps - Epsilon

    • Method Detail

      • getInputTypeRestriction

        public elki.data.type.TypeInformation[] getInputTypeRestriction()
        Specified by:
        getInputTypeRestriction in interface elki.Algorithm

      • run

        public OutlierResult run​(elki.database.relation.Relation<? extends elki.data.NumberVector> relation)
        Main loop for OUTRES
        Parameters:
        relation - Relation to process
        Returns:
        Outlier detection result

      • outresScore

        public double outresScore​(int s,
                          long[] subspace,
                          elki.database.ids.DBIDRef id,
                          OUTRES.KernelDensityEstimator kernel,
                          elki.database.ids.DBIDs cands)
        Main loop of OUTRES. Run for each object
        Parameters:
        s - start dimension
        subspace - Current subspace
        id - Current object ID
        kernel - Kernel
        cands - neighbor candidates
        Returns:
        Score

      • initialRange

        private elki.database.ids.DoubleDBIDList initialRange​(elki.database.ids.DBIDRef obj,
                                                      elki.database.ids.DBIDs cands,
                                                      elki.distance.PrimitiveDistance<? super elki.data.NumberVector> df,
                                                      double eps,
                                                      OUTRES.KernelDensityEstimator kernel,
                                                      elki.database.ids.ModifiableDoubleDBIDList n)
        Initial range query.
        Parameters:
        obj - Object
        cands - Candidates
        df - Distance function
        eps - Epsilon radius
        kernel - Kernel
        n - Output buffer
        Returns:
        Neighbors

      • subsetNeighborhoodQuery

        private elki.database.ids.DoubleDBIDList subsetNeighborhoodQuery​(elki.database.ids.DoubleDBIDList neighc,
                                                                 elki.database.ids.DBIDRef dbid,
                                                                 elki.distance.PrimitiveDistance<? super elki.data.NumberVector> df,
                                                                 double adjustedEps,
                                                                 OUTRES.KernelDensityEstimator kernel,
                                                                 elki.database.ids.ModifiableDoubleDBIDList n)
        Refine neighbors within a subset.
        Parameters:
        neighc - Neighbor candidates
        dbid - Query object
        df - distance function
        adjustedEps - Epsilon range
        kernel - Kernel
        n - Output list
        Returns:
        Neighbors of neighbor object

      • relevantSubspace

        protected boolean relevantSubspace​(long[] subspace,
                                   elki.database.ids.DoubleDBIDList neigh,
                                   OUTRES.KernelDensityEstimator kernel)
        Subspace relevance test.
        Parameters:
        subspace - Subspace to test
        neigh - Neighbor list
        kernel - Kernel density estimator
        Returns:
        relevance test result