• Title of article

    CAIMAN brothers: A family of powerful classification and class modeling techniques

  • Author/Authors

    Forina، نويسنده , , M. and Casale، نويسنده , , M. and Oliveri، نويسنده , , P. and Lanteri، نويسنده , , S.، نويسنده ,

  • Issue Information
    دوفصلنامه با شماره پیاپی سال 2009
  • Pages
    7
  • From page
    239
  • To page
    245
  • Abstract
    CAIMAN (Classification and Influence Matrix Analysis), a new classification technique, is here analyzed and modified to produce a number of possible classification and class modeling techniques with good performances in that regards both the prediction ability and the efficiency of the class models. These techniques are based on the addition to the original data matrix of the matrix of the Mahalanobis distances from the class centroids (or of the leverages, or of other distances). Then, the classical techniques of classification and class modeling are applied to the blocks of the predictors (original, added), separately or after fusion.
  • Keywords
    Classification , Mahalanobis distance , Leverage , Class modeling
  • Journal title
    Chemometrics and Intelligent Laboratory Systems
  • Serial Year
    2009
  • Journal title
    Chemometrics and Intelligent Laboratory Systems
  • Record number

    1489473