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CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
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Feature selection based on mutual information and redundancy-synergy coefficient
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YANG Sheng, GU Jun. Feature selection based on mutual information and redundancy-synergy coefficient[J]. Journal of Zhejiang University Science A, 2004, 5(11): 1382-1391.
@article{title="Feature selection based on mutual information and redundancy-synergy coefficient",
author="YANG Sheng, GU Jun",
journal="Journal of Zhejiang University Science A",
volume="5",
number="11",
pages="1382-1391",
year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.1382"
}
%0 Journal Article
%T Feature selection based on mutual information and redundancy-synergy coefficient
%A YANG Sheng
%A GU Jun
%J Journal of Zhejiang University SCIENCE A
%V 5
%N 11
%P 1382-1391
%@ 1869-1951
%D 2004
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2004.1382
TY - JOUR
T1 - Feature selection based on mutual information and redundancy-synergy coefficient
A1 - YANG Sheng
A1 - GU Jun
J0 - Journal of Zhejiang University Science A
VL - 5
IS - 11
SP - 1382
EP - 1391
%@ 1869-1951
Y1 - 2004
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2004.1382
Abstract: mutual information is an important information measure for feature subset. In this paper, a hashing mechanism is proposed to calculate the mutual information on the feature subset. Redundancy-synergy coefficient, a novel redundancy and synergy measure of features to express the class feature, is defined by mutual information. The information maximization rule was applied to derive the heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient. Our experiment results showed the good performance of the new feature selection method.
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