An Approach for Attribute Reduction and Rule Generation Based on Rough Set Theory
An Approach for Attribute Reduction and Rule Generation Based on Rough Set Theory
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发表时间：
1999
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通讯作者：
Li-yun Chang
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作者：
Li-yun Chang
在本文中，作者讨论了粗糙集研究中的两个重要问题：属性约简和值约简。提出了一种基于辨别矩阵和逻辑计算的属性约简新方法，能够达到最佳的属性约简。利用该方法可以得到一棵多元决策树。本文还对广泛使用的价值约简方法进行了一些改进。这样可以有效地降低所获取的规则知识的复杂度。
In this paper, the authors discuss two important issues in rough set research which are attributereduction and value reduction. A new attribute reduction approach which can reach the best attribute reductionis presented based on discernibility matrix and logic computation. And a multivariate decision tree can be gotwith this method. Some improvements for a widely used value reduction method are also achieved in this paper.The complexity of acquired rule knowledge can be reduced effectively in this way.