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
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