Using rough set in feature selection and reduction in face recognition problem
被引:0
作者:
Bac, LH
论文数: 0引用数: 0
h-index: 0
机构:
Univ Natl Sci, Fac Informat Technol, Ho Chi Minh City, VietnamUniv Natl Sci, Fac Informat Technol, Ho Chi Minh City, Vietnam
Bac, LH
[1
]
Tuan, NA
论文数: 0引用数: 0
h-index: 0
机构:
Univ Natl Sci, Fac Informat Technol, Ho Chi Minh City, VietnamUniv Natl Sci, Fac Informat Technol, Ho Chi Minh City, Vietnam
Tuan, NA
[1
]
机构:
[1] Univ Natl Sci, Fac Informat Technol, Ho Chi Minh City, Vietnam
来源:
ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
|
2005年
/
3518卷
关键词:
rough set;
feature selection;
feature reduction;
face recognition;
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:
Feature selection and reduction are fundamental steps in pattern recognition problems. The idea of reducts in rough set theory has encouraged many researchers in studying the effectiveness of rough set theory in the problem mentioned above. Through results of experiments in this article, we will show that rough set theory, accompanied by appropriate heuristics, can increase significantly the system's recognition accuracy.
引用
收藏
页码:226 / 233
页数:8
相关论文
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[Anonymous], 1991, EIGENFACES RECOGNITI
[2]
HOA NS, SOME EFFICIENT ALGOR
[3]
Komorowski J., ROUGH SETS TUTORIAL
[4]
Swiniarski R. W., 2001, International Journal of Applied Mathematics and Computer Science, V11, P565