Learning with Hierarchical Quantitative Attributes by Fuzzy Rough Sets
نویسندگان
چکیده
This paper proposes an approach to deal with the problem of producing a set of cross-level fuzzy certain and possible rules from examples with hierarchical and quantitative attributes. The proposed approach combines the rough-set theory and the fuzzy-set theory to learn. Some pruning heuristics are adopted in the proposed algorithm to avoid unnecessary search. A simple example is also given to illustrate the proposed approach.
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تاریخ انتشار 2006