An Empirical Comparison of Ideal and Empirical ROC Based Reject Rules 1st Edition by Claudio Marrocco, Mario Molinara, Francesco Tortorella 9783540734987
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Authors:Claudio Marrocco, Mario Molinara; Francesco Tortorella , Tags:Machine Learning and Data Mining in Pattern Recognition , Author sort:Claudio Marrocco, Mario Molinara & Tortorella, Francesco , Languages:Languages:eng , Comments:Comments:Machine Learning and Data Mining in Pattern Recognition
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ISBN 13: 9783540734987
Author: Claudio Marrocco, Mario Molinara; Francesco Tortorella
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.
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