Induction by Fuzzy Attribute Elimination
نویسنده
چکیده
A group of rules is belonging to one of the most popular, effective and userfriendly knowledge representation technologies. In this paper, a new direct method for making classification fuzzy rules on the basis of fuzzy attribute elimination is proposed. This elimination works with widely usable fuzzy attributes and eliminates them considering their unimportance determined by computing classification ambiguity. It helps to avoid irrelevant data in the induction process as soon as possible. Since integrating principles of fuzzy logics, it also allows to reduce uncertainty which is connected with real-world data. According to the comparisons with fuzzy decision tree and statistical methods, this approach achieves high accuracy levels of discovered knowledge.
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