文章基本信息

标题：Approach of Rule Extracting Based on Attribute Significance and Decision Classification
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作者：Zhai, Yandong ; Zhou, Chunguang ; Sun, Yingjuan 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2012
卷号：7
期号：2
页码：514-520
DOI：10.4304/jcp.7.2.514-520
语种：English
出版社：Academy Publisher
摘要：Propose a novel approach of rule extracting based on attribute significance and decision classification (REBSC). Condition attributes are only discretized with their own features in local discretization theory, and the eventual rule set normally can be achieved after attribute reduction. The REBSC approach given in this paper makes the most of each condition attribute significance and classification object, generates minimum decision rules without attribute reduction. Experiment one fully demonstrates the reasonability of the REBSC algorithm. Experiment two further proves its validity and testifies the significance of breakpoint division.
关键词：rough set; attribute significance; discretization; decision rule; attribute reduction