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The framework of axiomatics fuzzy sets based fuzzy classifiers
In this paper we will propose a new classifier design based
on the AFS fuzzy theory. First, we will briefly review the current
researches in data classification based on fuzzy and rough set theories and then
present the AFS framework. Second, we will present new
membership functions for fuzzy sets with their logic operations in the AFS
framework and then tackle some theoretical and computational problems related to classifier design. Third,
we will develop a new approach for fuzzy classifier
design based on the proposed membership functions and their logic
operations. Finally, a well-known example is
used to illustrate its effectiveness. The advantage of this classifier is in two-folds. One is
that it can mimic the human reasoning comprehensively and offers a far
more flexible and effective way for the study of large-scale
intelligent systems. The other is its simplicity in methodology and
mathematical beauty in fuzzy theory.