An Empirical Comparison of Ideal and Empirical ROC-Based Reject Rules
Two class classifiers are used in many complex problems in which the classification results could have serious consequences. In such situations the cost for a wrong classification can be so high that can be convenient to avoid a decision and reject the sample. This paper presents a comparison between two different reject rules (the Chow’s and the ROC rule). In particular, the experiments show that the Chow’s rule is inappropriate when the estimates of the a posteriori probabilities are not reliable.
KeywordsROC curve reject option two-class classification cost-sensitive classification decision theory
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