A GA-based Fuzzy Mining Approach to Achieve a Trade-off Between Number of Rules and Suitability of Membership Functions

Tzung-Pei Hong, Chun-Hao Chen, Yu-Lung Wu, Yeong-Chyi Lee
2006 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Data mining is most commonly used in attempts to induce association rules from transaction data. Transactions in real-world applications, however, usually consist of quantitative values. This paper thus proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions. We present a GA-based framework for finding membership functions suitable for mining problems and then use the final best set of membership functions to mine
more » ... association rules. The fitness of each chromosome is evaluated by the number of large 1-itemsets generated from part of the previously proposed fuzzy mining algorithm and by the suitability of the membership functions. Experimental results also show the effectiveness of the framework.
doi:10.1007/s00500-006-0046-x fatcat:uagegx4u7nhyxj5vwrz4tnb73i