On filling-in missing attribute values for Bayes and fuzzy classifiers

Abstract

Multidimensional classification problems often must address the issue of missing attribute values. The solution for this problem in the case of two frequency based classifiers is discussed here. The Bayes approach of boosting low frequency values, or filling-in missing values is compared to the interpolation operation used in the fuzzy classifiers.