Ant colony optimization combining with mutual information for feature selection in support vector machines

Authors:
Chunkai Zhang;Hong Hu
Affiliations:
Department of Mechanical Engineering and Automation, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China;Department of Mechanical Engineering and Automation, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

An effective feature selection scheme is proposed, which utilizes the combination of wrapper and filter: ant colony optimization (ACO) and mutual information (MI). By examining the modeling based on SVMs at the Australian Bureau of Meteorology, the simulation of three different methods of feature selection shows that the proposed method can reduce the dimensionality of inputs, speed up the training of the network and get better performance.