Discernibility matrix simplification with new attribute dependency functions for incomplete information systems

被引：12
|
作者：
Lang, Guangming [1 ]
Li, Qingguo [1 ]
Guo, Lankun [2 ]
机构：
[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
[2] Hunan Univ, Coll Informat Sci & Engn, Changsha 410082, Hunan, Peoples R China
来源：
KNOWLEDGE AND INFORMATION SYSTEMS | 2013年 / 37卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Rough set; Information system; Attribute dependency function; Discernibility matrix; ROUGH SET APPROACH; APPROXIMATION SPACES; DECISION SYSTEMS; REDUCTION; CONSISTENT; RULES;
D O I：
10.1007/s10115-012-0589-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Recently, many researches have been done on attribute dependency degree models. In this work, we bring forward three attribute dependency functions for incomplete information systems and investigate their basic properties in detail. Afterward, we apply the proposed models to twelve data sets from the UCI repository of machine learning databases. Finally, using the proposed functions, we perform the discernibility matrix simplification of incomplete information systems. The experimental results show that our proposed functions are more flexible to calculate the degree of each conditional attribute related to the decision attribute for incomplete information systems.
引用
收藏
页码：611 / 638
页数：28
相关论文
共 50 条
  • [1] Discernibility matrix simplification with new attribute dependency functions for incomplete information systems
    Guangming Lang
    Qingguo Li
    Lankun Guo
    [J]. Knowledge and Information Systems, 2013, 37 : 611 - 638
  • [2] Generalized binary discernibility matrix for attribute reduction in incomplete information systems
    Ma Fumin
    Zhang Tengfei
    [J]. The Journal of China Universities of Posts and Telecommunications, 2017, 24 (04) : 57 - 68
  • [3] Generalized binary discernibility matrix for attribute reduction in incomplete information systems
    [J]. Fumin, Ma (fmmatj@126.com), 2017, Beijing University of Posts and Telecommunications (24):
  • [4] Discernibility matrix simplification for constructing attribute reducts
    Yao, Yiyu
    Zhao, Yan
    [J]. INFORMATION SCIENCES, 2009, 179 (07) : 867 - 882
  • [5] Applying Restrained Genetic Algorithm for Attribute Reduction Using Attribute Dependency and Discernibility Matrix
    Das, Asit Kumar
    Chakrabarty, Saikat
    Pati, Soumen Kumar
    Sahaji, Ajijul Haque
    [J]. WIRELESS NETWORKS AND COMPUTATIONAL INTELLIGENCE, ICIP 2012, 2012, 292 : 299 - +
  • [6] Attribute Reduction Algorithm Based on Structure Discernibility Matrix in Composite Information Systems
    Ge, Mei-Jun
    Fan, Nian-Bai
    Sun, Tao
    [J]. 2017 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (IST 2017), 2017, 11
  • [7] A new algorithm for attribute reduction based on discernibility matrix
    Guan, Lihe
    [J]. FUZZY INFORMATION AND ENGINEERING, PROCEEDINGS, 2007, 40 : 373 - 381
  • [8] Comparative research of attribute reduction based on the new information entropy and on Skowron's discernibility matrix
    Xu, Zhangyan
    Qian, Wenbin
    Huang, Liyu
    Yang, Bingru
    [J]. PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 1, 2008, : 129 - +
  • [9] Attribute reduction in formal contexts based on a new discernibility matrix
    Qi, Jian-Jun
    [J]. JOURNAL OF APPLIED MATHEMATICS AND COMPUTING, 2009, 30 (1-2) : 305 - 314
  • [10] Attribute Reduction in Incomplete Information Systems
    Sun, Shibuo
    Duan, Jianhui
    Wanyan, Dandan
    [J]. ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PT III, 2011, 7004 : 587 - 594
12345