多类别属性的定序分类模型

doi:10.13190/jbupt.200903.113.zhuhd

北京邮电大学学报 ›› 2009, Vol. 32 ›› Issue (3): 113-117.doi: 10.13190/jbupt.200903.113.zhuhd

多类别属性的定序分类模型

朱颢东;钟勇

中国科学院成都计算机应用研究所

收稿日期:2008-10-24 修回日期:2009-02-21 出版日期:2009-06-28 发布日期:2009-06-28
通讯作者: 朱颢东

Sequencing Classification Model of Multiple Categories Attributes

ZHU Hao-Dong

Received:2008-10-24 Revised:2009-02-21 Online:2009-06-28 Published:2009-06-28
Contact: ZHU Hao-Dong

摘要/Abstract

摘要：

经典粗糙集方法是通过不可区分关系来获取知识的，但它对定性属性、定量属性以及准则属性同时出现的定序分类问题就显得无能为力。针对这种情况，给出一种基于扩展粗糙集的决策分析方法，该方法使用“不可区分-相似-优势”关系代替经典粗糙集中的不可区分关系来获取知识的粗糙近似，不但能够解决上述问题而且还能处理决策表中可能存在的不一致现象。最后通过一个实例说明新方法的有效性与优越性。

关键词: 粗糙集, 不可区分关系, 定序分类问题, 粗糙近似

Abstract:

Classic rough set approach acquires knowledge by means of indiscernibility relation, but it is powerless to resolve the sequencing classification problems which contain qualitative and quantitative attributes as well as criterias. In this case, a decision analysis method based on extension of rough set theory is proposed .This method replaces indiscernibility relation in original rough set theory with the “indiscernibility-similarity-dominance” relation and obtains rough approximation of knowledge, it will not only be able to resolve the aboved-mentioned problems but also deal with inconsistence in decision table. Finally, the effectiveness and superiority of the method are demonstrated by a real example.

Key words: Rough Set, Indiscernibility Relation, Sequencing Classification Problem, Rough Approximation

朱颢东;钟勇. 多类别属性的定序分类模型[J]. 北京邮电大学学报, 2009, 32(3): 113-117.

ZHU Hao-Dong. Sequencing Classification Model of Multiple Categories Attributes[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2009, 32(3): 113-117.

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多类别属性的定序分类模型

Sequencing Classification Model of Multiple Categories Attributes

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