Strongly selfguessing fuzzy classifiers

Article type: Research Article

Authors: Vatlin, Sergey

Affiliations: Belarusian State University of Informatics and Radioelectronics, 220027 Minsk, P. Brovka St. 6, Republic of Belarus

Abstract: The problem of construction of the fuzzy classification models (fuzzy classifiers) with high generalization ability is discussed. The strong self guessing property of fuzzy classificational models is introduced and examined. It is proved that this characteristic doesn't form a full system of restrictions, i.e., for the unambiguous detection of the most valid fuzzy classifier (among the set of fuzzy classifiers agreed with arbitrary learning set) it is necessary to use additional “regularizing” restrictions.

Keywords: fuzzy classifier, learning set, strongly selfguessing fuzzy classifier, generalized training sequence, generalized expansion of learning set, full system of restrictions

DOI: 10.3233/INF-1995-6106

Journal: Informatica, vol. 6, no. 1, pp. 85-92, 1995