J4 ›› 2006, Vol. 28 ›› Issue (6): 84-85.
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凌方[1] 范军[2]
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摘要：
鉴于实际应用中经常能遇到噪音的问题,本文通过对粗集方法的应用研究,提出规则的广义极大化方法,同时还提出了广义极大极小规则转换模型GMM.实验结果表明,采用该模型简化决策树规则既能简化单个规则,又能减少规则的总数量,更能排除数据中噪音的干扰,提高规则的分类精度.
关键词: 数据挖掘 粗集 噪音 知识约简
Abstract:
This paper puts forward rules-conversion model because we can sults illustrate that we can simplify the can solve the noise problem in practical a generalized maximal-rule-learning method and a generalized maximal-minimal always encounter noise problems in most real-world applications. Experimental re single rule as well as reduce the number of rules through the GMM method, and we applications effectively
Key words: data mining, rough set, noise, knowledge reduction
凌方[1] 范军[2]. 基于粗集的规则简化方法[J]. J4, 2006, 28(6): 84-85.
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http://joces.nudt.edu.cn/CN/Y2006/V28/I6/84
