haku: @author Erenguc, S. S. / yhteensä: 6
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Tekijä:Koehler, G. J.
Erenguc, S. S.
Otsikko:Minimizing misclassifications in linear discriminant analysis
Lehti:Decision Sciences
1990 : WINT. VOL. 21:1, p.63-83
Asiasana:MATHEMATICAL PROGRAMMING
MIXED INTEGER PROGRAMMING
Kieli:eng
Tiivistelmä:Discriminant analysis is used for two purposes: (1) to classify observations into mutually exclusive groups and (2) to explain differences between these groups based on observable attributes. The present paper develops a procedure for determining two-group linear discriminant classifiers that misclassify the minimal number of observations in the training examples. An experimental study confirms the value of the approach.
SCIMA tietueen numero: 80409
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