A New Rule Ranking Model for Associative Classification Using A Hybrid Artificial Intelligence Technique

摘要：

Rule ranking is a crucial step in Associative Classification (AC), AC algorithms proposed many ranking methods which aim to improve the accuracy of the classifier. In this paper we propose a new model in rule ranking, namely Hybrid-RuleRank, which employs a hybrid Artificial Intelligence (AI) technique that combines Simulated Annealing (SA) with Genetic Algorithm (GA), the new model tested against 11 data sets from UC1 Machine Learning Repository, and the experimental results show that our model enhances the accuracy of the classifier.

关键词： Associative Classification Artificial Intelligence Simulated Annealing Genetic Algorithm

作者: Moath M. Najeeb Asim El Sheikh Mohammed Nababteh

作者单位: Faculty of Information Systems and Technology The Arab Academy for Banking & Financial Sciences Amman, Jordan

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Information and Education Technology(ICIET 2011)(2011年信息和教育技术国际会议)

会议地点: 贵阳

会议语种:英文

页码: 231-235

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）