The 2ν-SVM: A Cost-Sensitive Extension of the ν-SVM

Abstract

Standard classification algorithms aim to minimize the probability of making an incorrect classification. In many important applications, however, some kinds of errors are more important than others. In this report we review cost-sensitive extensions of standard support vector machines (SVMs). In particular, we describe cost-sensitive extensions of the C… (More)

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Cite this paper

@inproceedings{Davenport2005The2A, title={The 2ν-SVM: A Cost-Sensitive Extension of the ν-SVM}, author={Mark A. Davenport}, year={2005} }