Rough Set Approximate Entropy Reducts With Order Based Particle Swarm Optimization

被引：0
|
作者：
Wang, Xiangyang [1 ]
Wan, Wanggen [1 ]
Yu, Xiaoqing [1 ]
机构：
[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200072, Peoples R China
来源：
WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) | 2009年
关键词：
Rough Set; Approximate Entropy Reducts; Particle Swarm Optimization; Order-based Particle Swarm Optimization; Hybrid Algorithm; FEATURE-SELECTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose an order-based Particle Swarm Optimization (o-PSO) hybrid algorithm for rough set approximate entropy reducts (oPSOAER). The o-PSO generates proper permutation of attributes, which are used by approximate entropy reduction algorithm to produce rough set reducts. The reducts are evaluated by fitness function. The primary criterion of optimization of the fitness function is the number of rules and the secondary is the reduct length. Our algorithm is tested on some UCI datasets. The results show that oSPOAER is efficient for approximate entropy reducts. The approximate entropy reducts optimized according to number of rules are better in classification algorithms than the shortest ones, and are much better for practical applications.
引用
收藏
页码：553 / 559
页数：7
相关论文
共 50 条
  • [41] A unified approach to reducts in dominance-based rough set approach
    Yoshifumi Kusunoki
    Masahiro Inuiguchi
    [J]. Soft Computing, 2010, 14 : 507 - 515
  • [42] Steganalysis Based on Feature Reducts of Rough Set by Using Genetic Algorithm
    Dai, Meng
    Liu, Yunxiang
    Lin, Jiajun
    [J]. 2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 6764 - +
  • [43] A Comprehensive Study on Reducts in Dominance-Based Rough Set Approach
    Kusunoki, Yoshifumi
    Inuiguchi, Masahiro
    [J]. MODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2008, 5285 : 167 - 178
  • [44] A unified approach to reducts in dominance-based rough set approach
    Kusunoki, Yoshifumi
    Inuiguchi, Masahiro
    [J]. SOFT COMPUTING, 2010, 14 (05) : 507 - 515
  • [45] Co-evolutionary Particle Swarm Optimization Based on Population Entropy
    Hu Chengyu
    Zhao Man
    Wang Yongji
    [J]. PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 5, 2008, : 70 - +
  • [46] Design of fractional order controllers based on particle swarm optimization
    Cao, Jun-yi
    Cao, Bing-gang
    [J]. 2006 1ST IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-3, 2006, : 69 - +
  • [47] Entropy based Binary Particle Swarm Optimization and classification for ear detection
    Ganesh, Madan Ravi
    Krishna, Rahul
    Manikantan, K.
    Ramachandran, S.
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 27 : 115 - 128
  • [48] Maximum Entropy for Image Segmentation based on an Adaptive Particle Swarm Optimization
    Qi, Chengming
    [J]. APPLIED MATHEMATICS & INFORMATION SCIENCES, 2014, 8 (06): : 3129 - 3135
  • [49] Threshold Selection Based on Fuzzy Tsallis Entropy and Particle Swarm Optimization
    Tang, Yinggan
    Di, Qiuyan
    Guan, Xinping
    Liu, Fucai
    [J]. NEUROQUANTOLOGY, 2008, 6 (04) : 412 - 419
  • [50] Hybrid Particle Swarm Optimization Algorithm Based on Intuitionistic Fuzzy Entropy
    Wang Y.
    Li X.-M.
    Geng G.-H.
    Zhou L.
    Duan Y.-Z.
    [J]. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2021, 49 (12): : 2381 - 2389
12345