Class KMeansOutlierDetection<O extends NumberVector>

  • Type Parameters:
    O - Object type
    All Implemented Interfaces:
    Algorithm, OutlierAlgorithm

    public class KMeansOutlierDetection<O extends NumberVector>
    extends java.lang.Object
    implements OutlierAlgorithm
    Outlier detection by using k-means clustering.

    The scores are assigned by the objects distance to the nearest center.

    We do not have a clear reference for this approach, but it seems to be a best practice in some areas to remove objects that have the largest distance from their center. This can for example be found mentioned in the book of Han, Kamber and Pei, but our implementation goes beyond their approach when it comes to handling singleton objects (that are a cluster of their own). To cite this approach, please cite the ELKI version you used (use the ELKI publication list for citation information and BibTeX templates).

    Erich Schubert