Class AggarwalYuNaive

  • All Implemented Interfaces:
    Algorithm, OutlierAlgorithm

    @Title("BruteForce: Outlier detection for high dimensional data")
    @Description("Examines all possible sets of k dimensional projections")
    @Reference(authors="C. C. Aggarwal, P. S. Yu",
               title="Outlier detection for high dimensional data",
               booktitle="Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD 2001)",
               url="https://doi.org/10.1145/375663.375668",
               bibkey="DBLP:conf/sigmod/AggarwalY01")
    public class AggarwalYuNaive
    extends AbstractAggarwalYuOutlier
    BruteForce variant of the high-dimensional outlier detection algorithm by Aggarwal and Yu.

    The evolutionary approach is implemented as AggarwalYuEvolutionary

    Reference:

    Outlier detection for high dimensional data
    C. C. Aggarwal, P. S. Yu
    Proc. 2001 ACM SIGMOD international conference on Management of data

    Since:
    0.4.0
    Author:
    Ahmed Hettab, Erich Schubert
    • Field Detail

      • LOG

        private static final Logging LOG
        The logger for this class.
    • Constructor Detail

      • AggarwalYuNaive

        public AggarwalYuNaive​(int k,
                               int phi)
        Constructor.
        Parameters:
        k - K
        phi - Phi
    • Method Detail

      • run

        public OutlierResult run​(Relation<? extends NumberVector> relation)
        Run the algorithm on the given relation.
        Parameters:
        relation - Relation
        Returns:
        Outlier detection result