document: A DEA approach for model combination This paper proposes a novel Data Envelopment Analysis ( DEA ) based approach for model combination . We first prove that for the 2-class classification problems DEA models identify the same convex hull as the popular ROC analysis used for model combination . For general k-class classifiers , we then develop a DEA-based method to combine multiple classifiers . Experiments show that the method outperforms other benchmark methods and suggest that DEA can be a promising tool for model combination .
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