CPDA Based Fuzzy Association Rules for Learning Achievement Mining

This paper proposes a fusion model to reinforce fuzzy association rules, which contains two main procedures: employing the Cumulative Probability Distribution Approach (CPDA) to partition the universe of discourse and build membership functions; and 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. Previous studies often partitioned the length of interval in equal-length and ignored the distribution characteristics of datasets.

Provided by: International Association of Computer Science & Information Technology (IACSIT) Topic: Software Date Added: May 2011 Format: PDF

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