Improvement of the consistent and strongly selfguessing fuzzy classifiers
Sergei Ivanovich Vatlin · 1997
Let Go and G 1 be arbitrary fuzzy classifiers (Vatlin, 1993). We say that G 1 improves Go iff the perfonnance of G 1 is more than Go one. We also introduced the concepts of consistent and strongly selfguessing fuzzy classifiers. The criterion of strong selfguessing is formulated. The theorems on the conditions of probabilistic improvement of consistent and mono tonic improvement of strongly selfguessing fuzzy classifiers are proved.