Fuzzy Set Theoretic Measure for Automatic Feature Evaluation

Abstract

The terms index of fuzziness, entropy, and π-ness, which give measures of fuzziness in a set, are used to define an index of feature evaluation in pattern recognition problems in terms of their intraclass and interclass measures. The index value decreases as the reliability of a feature in characterizing and discriminating different classes increases. The algorithm developed has been implemented in cases of vowel and plosive identification problem using formant frequencies and different S and π membership functions.