A classification rule mining method using hybrid genetic algorithms
Zhongyang Xiong, Zhang Lei, Yufang Zhang · 2004
In this paper, a classification method using an improved hybrid genetic algorithms combining (HGAc) with genetic algorithm and tabu search is presented. A rule extraction approach to raise the classification accuracy as well as to condense the classification rule set is also given. Finally, HGAc is validated upon four benchmark datasets and experimental results are compared with other algorithms. These experiments show that HGAc has good performance and is capable of discovering a set of the succinct, efficient and understandable classification rules.