Rule Discovery with Gene Expression Programming

摘要：

Data mining is becoming increasingly important since the size of database grows even larger and the need to explore hidden rules from the database becomes widely recognized. Gene expression programming is a full-fledged genotype/phenotype system that evolves computer programs encoded in linear chromosomes of fixed length. The structural organization of the linear chromosomes allows the unconstrained and fruitful (in the sense that no invalid phenotypes will follow) operation of important genetic operators such as mutation, transposition, and recombination as the expression of each gene always results in valid programs. In this paper, we introduced an association rule mining algorithm based on GEP and its implementation. Through the experiment results, we approved the algorithm is effective.

关键词： Data mining Gene expression programming association rule mining

作者: Qinghua Wu Dianhong Wang

作者单位: Faculty of Machine and Electronic Engineering, China University of Geosciences, Wuhan, 430074, China Faculty of Machine and Electronic Engineering, China University of Geosciences, Wuhan, 430074, China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）