CPDA Based Fuzzy Association Rules for Learning Achievement Mining
نویسندگان
چکیده
This paper proposes a fusion model to reinforce fuzzy association rules, which contains two main procedures: (1) employing the cumulative probability distribution approach (CPDA) to partition the universe of discourse and build membership functions; and (2) using the AprioriTid mining algorithm to extract fuzzy association rules. The proposed model is more objective and reasonable in determining the universe of discourse and membership functions with other fuzzy association rules.
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