DocumentCode
424132
Title
A new approach to feature subset selection
Author
Liu, Da-zhong ; Feng, Zhi-Jing ; Wang, Xi-Zhao
Author_Institution
Fac. of Math. & Comput. Sci., Hebei Univ., Baoding, China
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1822
Abstract
The paper presents a brief overview to the approaches of feature subset selection (FSS), commonly used in machine learning or pattern recognition. A combined algorithm based on the two algorithms, i.e., the mutual information selector (MIFS) and relevance information selector (RELFSS), is put forward. Experiments show some advantages of the combined algorithm.
Keywords
feature extraction; learning (artificial intelligence); set theory; feature subset selection; machine learning; mutual information selector; pattern recognition; relevance information selector; Entropy; Feature extraction; Frequency selective surfaces; Fuzzy sets; Machine learning; Machine learning algorithms; Mathematics; Measurement uncertainty; Mutual information; Scattering;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382072
Filename
1382072
Link To Document