Behaviormetrika
Online ISSN : 1349-6964
Print ISSN : 0385-7417
ISSN-L : 0385-7417
OPTIMAL LINEAR AND QUADRATIC CLASSIFIERS FOR TWO-GROUP DISCRIMINANT ANALYSIS
Yoshio Takane
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1987 Volume 14 Issue 21 Pages 97-110

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Abstract

A simple algorithm was developed for estimating optimal linear and quadratic classifiers (OLC & OQC) for non-normal multivariate predictor variables in two-group discriminant analysis. The algorithm is based on the alternating least squares (ALS) principle. The optimal classifiers compared favorably with the linear and quadratic discriminant function (LDF & QDF) methods in true error rate. Possible generalizations of the optimal classifier approach (ridge regression, robust regression based on the weighted least squares, etc.) were discussed.

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