DocumentCode
3399328
Title
A New Method for Feature Subset Selection for Handling Classification Problems
Author
Chen, Shyi-Ming ; Shie, Jen-Da
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei
fYear
2005
fDate
25-25 May 2005
Firstpage
183
Lastpage
188
Abstract
In this paper, we present a new method for dealing with feature subset selection for handling classification problems. We discriminate numeric features to construct the membership function of each fuzzy subset of each feature. Then, we select the feature subset based on the proposed fuzzy entropy measure with boundary samples. The proposed feature subset selection method cam select relevant features from sample data to get higher average classification accuracy rates than the ones selected by the existing methods
Keywords
entropy; feature extraction; fuzzy set theory; pattern classification; classification; feature subset selection; fuzzy entropy measure; fuzzy subset; membership function; numeric feature discrimination; Algorithm design and analysis; Classification algorithms; Computer science; Design methodology; Entropy; Filters; Fuzzy sets; Gain measurement; Genetic algorithms; Heuristic algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location
Reno, NV
Print_ISBN
0-7803-9159-4
Type
conf
DOI
10.1109/FUZZY.2005.1452390
Filename
1452390
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