DocumentCode :
2448071
Title :
Feature selection using a mutual information based measure
Author :
Al-Ani, Ahmed ; Deriche, Mohamed
Author_Institution :
Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume :
4
fYear :
2002
fDate :
2002
Firstpage :
82
Abstract :
In this paper, we discuss the problem of feature selection for the purpose of classification and propose a solution based on the concept of mutual information. In addition, we propose a new evaluation function to measure the ability of feature subsets in distinguishing between class labels. The proposed function is based on the information gain taking into consideration how features work. Finally, we discuss the performance of this function compared to that of other measures which evaluate features individually.
Keywords :
entropy; feature extraction; pattern classification; classification accuracy; entropy; feature selection; image texture; mutual information; pattern classification; Australia; Classification algorithms; Entropy; Filters; Gain measurement; Mutual information; Performance gain; Random variables; Signal processing; Velocity measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1047405
Filename :
1047405
Link To Document :
بازگشت