Decision rule mining using classification consistency rate

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• 作者：Jianhua Dai ; ^{jhdai@cs.zju.edu.cn} ; Haowei Tian ; Wentao Wang ; Liang Liu
• 关键词：Decision rules ; Rule learning ; Rough sets ; Inconsistent decision tables ; Classification consistency rate
• 刊名：Knowledge-Based Systems
• 出版年：2013
• 出版时间：May, 2013
• 年：2013
• 卷：43
• 期：Complete
• 页码：95-102
• 全文大小：631 K

文摘

Decision rule mining is an important technique in many applications. In this paper, we propose a new rough set approach for rule induction based on a significance measure, called classification consistency rate. The approach implements the rule induction from the viewpoint of attribute rather than descriptor. The proposed algorithm is tested and compared with LEM2 algorithm on several real-life data sets added with different levels of inconsistent data. The results show that the proposed algorithm is effective in rule induction for inconsistent data.