A novel algorithm for attribute reduction based on consistency criterion

被引：3
|
作者：
Yang M. [1 ,2 ]
机构：
[1] School of Computer Science and Technology, Nanjing Normal University
[2] Jiangsu Research Center of Information Security and Privacy Technology
来源：
Jisuanji Xuebao/Chinese Journal of Computers | 2010年 / 33卷 / 02期
关键词：
Attributes reduction; Consistency criterion; Rough set;
D O I：
10.3724/SP.J.1016.2010.00231
中图分类号：
学科分类号：
摘要：
Rough set theory is a new mathematical tool to deal with imprecise, incomplete and inconsistent data. Attribute reduction is one of important parts researched in rough set theory. Many existing algorithms mainly aim at the reduction of discrete-valued attributes, very little work has been done for attribute reduction aiming to continuous-valued attributes. Therefore, in this paper, after introducing a new definition on consistency of objects, a novel model based on consistency criterion for attribute reduction is introduced. The newly designed model is very suitable for the decision table with discrete-valued or continuous-valued attributes, and an extension of the classical rough set model. Based on this model, a novel algorithm for attribute reduction based on consistency criterion is proposed. This algorithm can effectively obtain an attribute reduction for the decision table with continuous-valued attributes, and meanwhile the effectiveness of the attribute subset obtained by the new model can be enhanced by controlling the number of the misclassified or consistent objects. Theoretical analysis and experiments shows that the algorithm of this paper is efficient and feasible.
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收藏
页码：231 / 239
页数：8
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