A novel associative classification model based on a fuzzy frequent pattern mining algorithm

作者：

Highlights：

• We propose a novel efficient fuzzy associative classification approach.

• We exploit a fuzzy version of the FP-Growth algorithm.

• We perform an experimental analysis on 17 classification datasets.

• We compare our approach with three well-known associative classifiers.

摘要

•We propose a novel efficient fuzzy associative classification approach.•We exploit a fuzzy version of the FP-Growth algorithm.•We perform an experimental analysis on 17 classification datasets.•We compare our approach with three well-known associative classifiers.

论文关键词：Fuzzy association rule-based classifiers,Fuzzy FP-Growth,Fuzzy associative classifier,Fuzzy association rules

论文评审过程：Available online 23 October 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.09.021