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Feature selection for multi-class classification using support vector data description

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3 Author(s)
Daun Jeong ; Grad. Inst. of Ferrous Technol., POSTECH, Pohang, South Korea ; Dongyeop Kang ; Sangchul Won

In this paper, a supervised feature selection approach is presented, which is based on support vector data description(SVDD). This method is suggested for multi-class classification case, and it utilizes a sequential backward selection algorithm using the accuracy of classifier to decide which feature to be eliminated. The proposed approach is applied to well-known real world datasets, and the obtained results are compared with results from the existing feature selection techniques. Simulation results demonstrate the effectiveness of the proposed method.

Published in:

IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society

Date of Conference:

7-10 Nov. 2010