Abstract :
Abstract—In this paper a least-square approach to multiclass pattern classification is undertaken. The generalized inverse computation is used to furnish a quick solution to the problem of fixed training samples. The use of recursive on-line computation is also recommended. Experimental results are presented to illustrate the approach. Both deterministic and statistical interpretations have been given to the approach. The pattern classifier proposed by Chaplin and Levadi [1] and the adaptive pattern classifier proposed by Patterson and Womack [2] are special cases of this approach.
Keywords :
Index Terms—Adaptation, discriminant functions, generalized inverse, mapping interpretation, optimum Bayes procedure, pattern classification.; Approximation methods; Costs; Data analysis; H infinity control; Pattern classification; Polynomials; Stochastic processes; Index Terms—Adaptation, discriminant functions, generalized inverse, mapping interpretation, optimum Bayes procedure, pattern classification.;
