GA-based pattern classification: theoretical and experimental studies
S. Bandyopadhyay, C.A. Murthy, Saptarshi Pal · 1996
Merits of genetic algorithms (GAs), an efficient evolutionary searching paradigm, are utilized for pattern classification in /spl Rfr//sup N/ by fitting hyperplanes to model the decision boundaries in the feature space. Theoretical analysis establishes that as the size of the training set (n) goes towards infinity, the error probability and the decision boundary of the GA based classifier will approach those of Bayes (optimum) classifier.