Class RandomSampleKNNPreprocessor<O>

  • Type Parameters:
    O - Object type
    All Implemented Interfaces:
    Index, KNNIndex<O>

    @Reference(authors="Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, J\u00f6rg Sander",
               title="Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles",
               booktitle="Proc. 19th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, KDD \'13",
               url="https://doi.org/10.1145/2487575.2487676",
               bibkey="DBLP:conf/kdd/ZimekGCS13")
    public class RandomSampleKNNPreprocessor<O>
    extends AbstractMaterializeKNNPreprocessor<O>
    Class that computed the kNN only on a random sample.

    Used in:

    Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, Jörg Sander
    Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles
    Proc. 19th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining KDD'13

    Since:
    0.5.0
    Author:
    Erich Schubert