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
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;
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
DOI :
10.1109/CIT.2007.81