Multi-class classification using a signomial function

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.

Keywords:

• multi-class classification
• signomial function
• sparse classifier
• column generation algorithm

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012–006351).