An evolutionary based multi-objective filter approach for feature selection

Labani, M, Moradi, P, Jalili, M and Yu, X 2017, 'An evolutionary based multi-objective filter approach for feature selection', in Proceedings of the 2nd World Congress on Computing and Communication Technologies (WCCCT 2017), Tiruchirappalli, Tamil Nadu, India, 2-4 February 2017, pp. 151-154.


Document type: Conference Paper
Collection: Conference Papers

Title An evolutionary based multi-objective filter approach for feature selection
Author(s) Labani, M
Moradi, P
Jalili, M
Yu, X
Year 2017
Conference name WCCCT 2017
Conference location Tiruchirappalli, Tamil Nadu, India
Conference dates 2-4 February 2017
Proceedings title Proceedings of the 2nd World Congress on Computing and Communication Technologies (WCCCT 2017)
Publisher IEEE
Place of publication United States
Start page 151
End page 154
Total pages 4
Abstract Feature selection is one of the important research areas in pattern recognition. The aim of feature selection is to select those of informative features to improve the classifier's performance. In this paper, we propose a novel multi-objective algorithm based on mutual information for feature selection, called multi-objective mutual information (MOMI). The proposed method identifies a set of features with minimal redundancy and maximum relevancy with the target class. Several experiments are performed to evaluate the performance of MOMI compared to that of well-known and state-of-the-art feature selection methods over five benchmark datasets. The results show that in most cases MOMI achieves better classification performance than others.
Subjects Dynamical Systems in Applications
Artificial Intelligence and Image Processing not elsewhere classified
Keyword(s) multi-objective optimization
mutual information
feature selection
dimensionality reduction
DOI - identifier 10.1109/WCCCT.2016.44
Copyright notice © 2017 IEEE
ISBN 9781509055746
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