计算机应用 ›› 2016, Vol. 36 ›› Issue (11): 2954-2957.DOI: 10.11772/j.issn.1001-9081.2016.11.2954

• 第十六届中国粗糙集与软计算联合学术会议(CRSSC 2016)论文 • 上一篇    下一篇

变精度粗糙集的区域属性约简及其结构启发算法

熊方1, 张贤勇2   

  1. 1. 四川现代职业学院 电子信息技术系, 成都 610207;
    2. 四川师范大学 数学与软件科学学院, 成都 610068
  • 收稿日期:2016-06-07 修回日期:2016-06-21 出版日期:2016-11-10 发布日期:2016-11-12
  • 通讯作者: 熊方
  • 作者简介:熊方(1981-),女,四川资阳人,讲师,硕士,主要研究方向:粗糙集、数据挖掘;张贤勇(1978-),男,四川宜宾人,副教授,博士,主要研究方向:粗糙集、粒计算、三支决策。
  • 基金资助:
    国家自然科学基金资助项目(61203285);四川省教育厅科研项目(15ZB0028)。

Regional attribute reduction and their structural heuristic algorithms for variable precision rough sets

XIONG Fang1, ZHANG Xianyong2   

  1. 1. Department of Electronics and Information Technology, Sichuan Modern Vocational College, Chengdu Sichuan 610207, China;
    2. College of Mathematics and Software Science, Sichuan Normal University, Chengdu Sichuan 610068, China
  • Received:2016-06-07 Revised:2016-06-21 Online:2016-11-10 Published:2016-11-12
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61203285), the Scientific Research Project of Sichuan Provincial Education Department (15ZB0028).

摘要: 采用二分类情形与三支决策区域,研究变精度粗糙集(VPRS)两类属性约简及其结构启发算法。首先,依托三支决策区域构建分类区域,提出分类区域保持(CRP)约简与决策区域保持(DRP)约简,得到对定性属性约简的量化扩张性,设计基于核的结构启发算法;然后,研究两类区域约简的强弱关系,设计由强至弱的结构启发算法,得到二支决策拓展为三支决策的约简改进;最后,利用数据表实例与UCI数据集验证区域约简及其启发算法的有效性。

关键词: 变精度粗糙集, 属性约简, 三支决策, 结构启发算法

Abstract: According to the two-category case and three-way decision regions, two types of attribute reductions for Variable Precision Rough Sets (VPRS) and their structural heuristic algorithms were studied. First of all, classification-regions were constructed by three-way decision regions, and Classification-Region Preservation (CRP) reduction and Decision-Region Preservation (DRP) reduction were proposed, quantitative expansion of the qualitative attribute reduction was obtained, and the structural heuristic algorithms based on cores were designed. Furthermore, the strong-weak relationships between the two kinds of regional reductions were studied, and structural heuristic algorithms from strong to weak were designed to achieve improvement from the two-way to three-way decisions. Finally, the validity of the relevant reductions and algorithms were verified by the data table and UCI data set.

Key words: Variable Precision Rough Set (VPRS), attribute reduction, three-way decision, structural heuristic algorithm

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