Importance degree of features and feature selection

Authors:
Di Xiao;Junfeng Zhang
Affiliations:
School of Automation & Electrical Engineering, Nanjing University of Technology, Nanjing, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Year:
2009

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Abstract

A novel measure, importance degree of features, is proposed to rank the features. And a new filter method is presented to carry out feature selection based on such measure. The monotonic property of this proposed measure can reduce the search space, which results in enhancing learning efficiency. The simulation results indicate the validity of our method.