Feature Selection Algorithm Based on Association Rules Mining Method

Authors:
Jianwen Xie;Jianhua Wu;Qingquan Qian
Affiliations:
-;-;-
Venue:
ICIS '09 Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science
Year:
2009

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Abstract

This paper presents a novel feature selection algorithm based on the technique of mining association rules. The main idea of the proposed algorithm is to find the features that are closely correlative with the class attribute by association rules mining method. Experimental results on several real and artificial data sets demonstrate that the proposed feature selection algorithm is able to obtain a smaller and satisfactory feature subset when compared with other existing feature selection algorithms. It is a new feature selection algorithm with vast of application prospect and research value.