An Efficient SFL-Based Classification Rule Mining Algorithm

摘要：

Classification rule mining is an important data mining process that aims to discover a small set of rules from the training data set with predetermined targets.The shuffled frog leaping(SFL) algorithm, is a new robust evohttionary algorithm based on the local search and the shuffling processes. In this paper, an efficient SFL-based classification rule mining algorithm is proposed. The experimental results show that the proposed algorithm performs much better than other related algorithms.

作者: Hui Yin Fengjuan Cheng Chunjie Zhou

作者单位: Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan 43 School of Information Science and Engineering,Henan University of Technology,Zhengzhou 450001,China Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan 43

会议类型: 国际会议

会议名称: 2008 IEEE International Symposium on IT in Medicine and Education(2008信息技术在医学和教育中的应用国际研讨会)(ITME 2008)

会议地点: 厦门

会议语种:英文

页码: 969-972

在线出版日期: 2008-12-12（万方平台首次上网日期，不代表论文的发表时间）