DocumentCode
2139175
Title
An Experimental Study on Feature Subset Selection Methods
Author
Yun, Chulmin ; Shin, Donghyuk ; Jo, Hyunsung ; Yang, Jihoon ; Kim, Saejoon
Author_Institution
Sogang Univ., Seoul
fYear
2007
fDate
16-19 Oct. 2007
Firstpage
77
Lastpage
82
Abstract
In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some feature selection algorithms and analyze their performance using various datasets from public domain. We measured the number of reduced features and the improvement of learning performance with chosen feature selection methods, then evaluated and compared each method on the basis of these measurements.
Keywords
learning (artificial intelligence); feature subset selection methods; learning performance; machine learning; pattern recognition; Algorithm design and analysis; Computational efficiency; Computer science; Costs; Information technology; Learning systems; Machine learning; Machine learning algorithms; Pattern recognition; Performance analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on
Conference_Location
Aizu-Wakamatsu, Fukushima
Print_ISBN
978-0-7695-2983-7
Type
conf
DOI
10.1109/CIT.2007.81
Filename
4385060
Link To Document