Class SimilarityNeighborPredicate<O>

  • Type Parameters:
    O - object type
    All Implemented Interfaces:
    NeighborPredicate<elki.database.ids.DoubleDBIDList>

    @Reference(authors="Martin Ester, Hans-Peter Kriegel, J\u00f6rg Sander, Xiaowei Xu",
               title="A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise",
               booktitle="Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD \'96)",
               url="http://www.aaai.org/Library/KDD/1996/kdd96-037.php",
               bibkey="DBLP:conf/kdd/EsterKSX96")
    public class SimilarityNeighborPredicate<O>
    extends java.lang.Object
    implements NeighborPredicate<elki.database.ids.DoubleDBIDList>
    The DBSCAN neighbor predicate for a Similarity, using all neighbors with a minimum similarity.

    Reference:

    Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu
    A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise
    Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD '96)

    Since:
    0.7.5
    Author:
    Erich Schubert
    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected double epsilon
      Range to query with
      protected elki.similarity.Similarity<? super O> simFunc
      Similarity function to use
    • Constructor Summary

      Constructors 
      Constructor Description
      SimilarityNeighborPredicate​(double epsilon, elki.similarity.Similarity<? super O> simFunc)
      Full constructor.
    • Field Detail

      • epsilon

        protected double epsilon
        Range to query with
      • simFunc

        protected elki.similarity.Similarity<? super O> simFunc
        Similarity function to use
    • Constructor Detail

      • SimilarityNeighborPredicate

        public SimilarityNeighborPredicate​(double epsilon,
                                           elki.similarity.Similarity<? super O> simFunc)
        Full constructor.
        Parameters:
        epsilon - Epsilon value
        simFunc - Similarity function to use