| 基于二进制可辨矩阵属性重要度的属性约简算法 |
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| 引用本文： | 汪小燕. 基于二进制可辨矩阵属性重要度的属性约简算法[J]. 安徽工业大学学报, 2007, 24(1): 76-78,97 |
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| 作者姓名： | 汪小燕 |
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| 作者单位： | 安徽工业大学,计算机学院,安徽,马鞍山,243002 |
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| 摘 要： | 粗糙集理论是一个新的数据挖掘方法,是在保持分类能力不变的情况下,利用等价类,通过属性约简和规则约简,达到挖掘知识并简化知识的目的.但属性约简是一个NP难题,需要通过启发式知识实现.文中提出了一种利用二进制可辨矩阵的属性重要度实现属性约简的算法,该算法能快速求最少属性且实现简单,并通过理论和实例证明了其正确性.
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| 关 键 词： | 粗糙集 二进制可辨矩阵 属性约简 |
| 文章编号： | 1671-7872（2007）01-0076-03 |
| 收稿时间： | 2006-03-13 |
| 修稿时间： | 2006-03-13 |
Algorithm for Attribute Reduction Based on Attribute Significance of Binary Discernible Matrix |
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| WANG Xiao-yan. Algorithm for Attribute Reduction Based on Attribute Significance of Binary Discernible Matrix[J]. Journal of Anhui University of Technology, 2007, 24(1): 76-78,97 |
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| Authors: | WANG Xiao-yan |
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| Abstract: | Rough set theory is a new method of data mining.Its basic thought is utilizing equivalence relation class,through attribution reduction and rule reduction,to excavate knowledge and reduce knowledge.But the attribution reduction is a NP problem,and it needs to be realized by knowledge of elicitation method. The algorithm for attribute reduction based on attribute significance of binary discernible matrix is proposed. The algorithm can get the smallest attributes quickly and be realized easily. And it is proved to be workable in the theory and practice. |
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| Keywords: | rough set binary discernable matrix attribute reduction |
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