Multi-class classification using a signomial function

Kyoungmi Hwang, Kyungsik Lee, Chungmok Lee and Sungsoo Park
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Kyoungmi Hwang: KAIST, Daejeon, Korea (South), Republic of Korea
Kyungsik Lee: Seoul National University, Seoul, Republic of Korea; Hankuk University of Foreign Studies, Yongin-si, Republic of Korea
Chungmok Lee: IBM Research—Ireland, Dublin, Ireland
Sungsoo Park: KAIST, Daejeon, Korea (South), Republic of Korea

Journal of the Operational Research Society, 2015, vol. 66, issue 3, 434-449

Abstract: We propose two multi-class classification methods using a signomial function. Each of these methods directly constructs a multi-class classifier by solving a single optimization problem. Since the number of possible signomial terms is extremely large, we propose a column generation method that iteratively generates good signomial terms. Both of these methods obtain better or comparable classification accuracies than existing methods and also provide more sparse classifiers.

Date: 2015
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