MEAN ACCURACY OF PATTERN RECOGNIZERS WITH MANY PATTERN CLASSES

Hughes [1] presented some curves relating the mean performance of a pattern classifier averaged over all pattern recognition problems of given complexity, when there are two classes of patterns to be distinguished. In this correspondence the mean recognition probability is computed for the case of q pattern classes when the a priori probabilities of the classes are equal. When the a priori probabilities are unequal, the mean performance will improve over the performance with equal a priori probabilities, so these curves provide a lower bound to the performance of recognizers with more than two pattern classes. Some comments on the appropriateness of these statistics to common recognition problems are made. © 1969 IEEE. All rights reserved.