Utilizing non-uniform cost learning for active control of inter-class confusion
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In this paper, we demonstrate the use of learning with non-uniform error-cost as a novel technique to design a multiclass cost-sensitive classifier. We investigate two important aspects of the design. First, we show that the learning is effective enough for active control of the multiclass confusion matrix using the cost-matrix. Second, we study the cases when the classifiers have mild model mismatch problems, and conclude that our design still have better performance compared to the conventional cost-sensitive classifier design.
[1] Dwi Sianto Mansjur,et al. Non-Uniform error criteria for automatic pattern and speech recognition , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[2] Charles Elkan,et al. The Foundations of Cost-Sensitive Learning , 2001, IJCAI.
[3] Guido Dedene,et al. Cost-sensitive learning and decision making revisited , 2005, Eur. J. Oper. Res..