A GMM-Based Feature Selection Algorithm for Multi-Class Classification

International Journal
2009-08-01 14:47
Authors : Tacksung Choi, Sunkuk Moon, Young-Cheol Park, Dea Hee Youn, Seokpil Lee

Year : 2009

Publisher / Conference : IEICE Transactions on Information and Systems

Volume : E92-D. No.8

Page : 1584-1587

In this paper, we propose a new feature selection algorithm for multi-class classification. The proposed algorithm is based on Gaussian mixture models (GMMs) of the features, and it uses the distance between the two least separable classes as a metric for feature selection. The proposed system was tested with a support vector machine (SVM) for multi-class classification of music. Results show that the proposed feature selection scheme is superior to conventional schemes.
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