Feature Selection Based on Ant Colony Optimization and Rough Set Theory

被引：5
|
作者：
He, Ming [1 ]
机构：
[1] Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China
来源：
ISCSCT 2008: INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND COMPUTATIONAL TECHNOLOGY, VOL 1, PROCEEDINGS | 2008年
关键词：
rough set; ant colony optimization; feature selection; core;
D O I：
10.1109/ISCSCT.2008.43
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. Rough set theory offers a viable approach for feature selection from data sets. In this paper, the basic concepts of rough set theory and ant colony optimization are introduced, and the role of the basic constructs of rough set approach in feature selection, namely attribute reduction is studied. Base above research, a rough set and ACO based algorithm for feature selection problems is proposed. Finally, the presented algorithm was tested on UCI data sets and performed effectively.
引用
收藏
页码：247 / 250
页数：4
相关论文
共 50 条
  • [21] Text feature selection using ant colony optimization
    Aghdam, Mehdi Hosseinzadeh
    Ghasem-Aghaee, Nasser
    Basiri, Mohammad Ehsan
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) : 6843 - 6853
  • [22] A New Hybrid Ant Colony Optimization Based on Brain Storm Optimization for Feature Selection
    Liang, Haomo
    Wang, Zhixue
    Liu, Yi
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2019, E102D (07): : 1396 - 1399
  • [23] An Improved Feature Selection Algorithm Based on Ant Colony Optimization
    Peng, Huijun
    Ying, Chun
    Tan, Shuhua
    Hu, Bing
    Sun, Zhixin
    IEEE ACCESS, 2018, 6 : 69203 - 69209
  • [24] An approach for selective ensemble feature selection based on rough set theory
    Yang, Yong
    Wang, Guoyin
    He, Kun
    ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS, 2007, 4481 : 518 - +
  • [25] A wrapper-filter feature selection technique based on ant colony optimization
    Manosij Ghosh
    Ritam Guha
    Ram Sarkar
    Ajith Abraham
    Neural Computing and Applications, 2020, 32 : 7839 - 7857
  • [26] An improved feature selection algorithm based on graph clustering and ant colony optimization
    Ghimatgar, Hojat
    Kazemi, Kamran
    Helfroush, Mohamamd Sadegh
    Aarabi, Ardalan
    KNOWLEDGE-BASED SYSTEMS, 2018, 159 : 270 - 285
  • [27] A wrapper-filter feature selection technique based on ant colony optimization
    Ghosh, Manosij
    Guha, Ritam
    Sarkar, Ram
    Abraham, Ajith
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (12) : 7839 - 7857
  • [28] A new hybrid ant colony optimization algorithm for feature selection
    Kabir, Md. Monirul
    Shahjahan, Md.
    Murase, Kazuyuki
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (03) : 3747 - 3763
  • [29] Enriched ant colony optimization and its application in feature selection
    Forsati, Rana
    Moayedikia, Alireza
    Jensen, Richard
    Shamsfard, Mehrnoush
    Meybodi, Mohammad Reza
    NEUROCOMPUTING, 2014, 142 : 354 - 371
  • [30] Ant Colony Optimization with Null Heuristic Factor for Feature Selection
    Oh, Il-Seok
    Lee, Jin-Seon
    TENCON 2009 - 2009 IEEE REGION 10 CONFERENCE, VOLS 1-4, 2009, : 140 - +
12345