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A classification method of fuzzy association rules

Partition method of interval is adopted in current classification based on associations (CBA), but this method cannot reflect the actual distribution of data and exists the problem of sharp boundary. Quantitative attributes are partitioned into several fuzzy sets by fuzzy c-means algorithm, and search technology of Apriori algorithm is improved to discover interesting fuzzy association rules, which are used to build classification system. Because fuzzy c-means algorithm can embody the actual distribution of the data and fuzzy sets can soften partition boundary, the classification system of the fuzzy association rules can obtain better classification accuracy than two popular classification methods: C4.5 and CBA