Package elki.outlier.distance

Class LocalIsolationCoefficient<O>

  • Type Parameters:
    O - the type of objects handled by this algorithm
    All Implemented Interfaces:
    elki.Algorithm, OutlierAlgorithm
    @Reference(authors="B. Yu, M. Song, L. Wang",
           title="Local Isolation Coefficient-Based Outlier Mining Algorithm",
           booktitle="Int. Conf. on Information Technology and Computer Science (ITCS) 2009",
           url="https://doi.org/10.1109/ITCS.2009.230",
           bibkey="doi:10.1109/ITCS.2009.230")
public class LocalIsolationCoefficient<O>
extends java.lang.Object
implements OutlierAlgorithm
    The Local Isolation Coefficient is the sum of the kNN distance and the average distance to its k nearest neighbors.

    The algorithm originally used a normalized Manhattan distance on numerical attributes, and Hamming distance on categorial attributes.

    Reference:

    B. Yu, M. Song, L. Wang
    Local Isolation Coefficient-Based Outlier Mining Algorithm
    Int. Conf. on Information Technology and Computer Science (ITCS) 2009

    Since:
    0.7.0
    Author:
    Erich Schubert

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      static class  LocalIsolationCoefficient.Par<O>
      Parameterization class.

      • Nested classes/interfaces inherited from interface elki.Algorithm

        elki.Algorithm.Utils

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected elki.distance.Distance<? super O> distance
      Distance function used.
      private int kplus
      Holds the number of nearest neighbors to query (plus the query point!)
      private static elki.logging.Logging LOG
      The logger for this class.

    • Constructor Summary

      Constructors 
      Constructor Description
      LocalIsolationCoefficient​(elki.distance.Distance<? super O> distance, int k)
      Constructor with parameters.

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      elki.data.type.TypeInformation[] getInputTypeRestriction()  
      OutlierResult run​(elki.database.relation.Relation<O> relation)
      Runs the algorithm in the timed evaluation part.

      • 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.

      • kplus

        private int kplus
        Holds the number of nearest neighbors to query (plus the query point!)

      • distance

        protected elki.distance.Distance<? super O> distance
        Distance function used.

    • Constructor Detail

      • LocalIsolationCoefficient

        public LocalIsolationCoefficient​(elki.distance.Distance<? super O> distance,
                                 int k)
        Constructor with parameters.
        Parameters:
        distance - Distance function
        k - k Parameter (not including query point!)

    • Method Detail

      • getInputTypeRestriction

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

      • run

        public OutlierResult run​(elki.database.relation.Relation<O> relation)
        Runs the algorithm in the timed evaluation part.
        Parameters:
        relation - Data relation