The incremental method for fast computing the rough fuzzy approximations

被引:81
作者
Cheng, Yi [1 ]
机构
[1] Sichuan Coll Architectural Technol, Dept Equipment & Engn, Deyang 618000, Peoples R China
关键词
Rough fuzzy sets; Lower approximation; Upper approximation; Knowledge discovery; Data mining; SET;
D O I
10.1016/j.datak.2010.08.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The lower and upper approximations are basic concepts in rough fuzzy set theory. The effective computation of approximations is very important for improving the performance of related algorithms. This paper proposed and proved two incremental methods for fast computing the rough fuzzy approximations, one starts from the boundary set, the other is based on the cut sets of a fuzzy set Then some illustrative examples are conducted. Consequently, two algorithms corresponding to the two incremental methods are put forward respectively. In order to test the efficiency of algorithms, some experiments are made on a large soybean data set from UCI. The experimental results show that the two incremental methods effectively reduce the computing time in comparison with the traditional non-incremental method [1]. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:84 / 100
页数:17
相关论文
共 41 条
  • [1] [Anonymous], 1999, ROUGH FUZZY HYBRIDIZ
  • [2] A rough fuzzy approach to web usage categorization
    Asharaf, S
    Murty, MN
    [J]. FUZZY SETS AND SYSTEMS, 2004, 148 (01) : 119 - 129
  • [3] An adaptive rough fuzzy single pass algorithm for clustering large data sets
    Asharaf, S
    Murty, MN
    [J]. PATTERN RECOGNITION, 2003, 36 (12) : 3015 - 3018
  • [4] Roughness of a fuzzy set
    Banerjee, M
    Pal, SK
    [J]. INFORMATION SCIENCES, 1996, 93 (3-4) : 235 - 246
  • [5] Towards incremental fuzzy classifiers
    Bouchachia, Abdelhamid
    Mittermeir, Roland
    [J]. SOFT COMPUTING, 2007, 11 (02) : 193 - 207
  • [6] Fuzziness in rough sets
    Chakrabarty, K
    Biswas, R
    Nanda, S
    [J]. FUZZY SETS AND SYSTEMS, 2000, 110 (02) : 247 - 251
  • [7] CHAN C, 1998, INFORM SCI, V107, P177
  • [8] Chen Y, 2006, PROCEEDINGS OF THE FIFTH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS, VOLS 1 AND 2, P835
  • [9] ROUGH FUZZY-SETS AND FUZZY ROUGH SETS
    DUBOIS, D
    PRADE, H
    [J]. INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 1990, 17 (2-3) : 191 - 209
  • [10] Feng T, 2006, LECT NOTES ARTIF INT, V4062, P208