An Empirical Comparison of Ideal and Empirical ROC-Based Reject Rules

Authors:
Claudio Marrocco;Mario Molinara;Francesco Tortorella
Affiliations:
DAEIMI, Università degli Studi di Cassino, Via G. Di Biasio 43, 03043 Cassino (FR), Italia;DAEIMI, Università degli Studi di Cassino, Via G. Di Biasio 43, 03043 Cassino (FR), Italia;DAEIMI, Università degli Studi di Cassino, Via G. Di Biasio 43, 03043 Cassino (FR), Italia
Venue:
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2007

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Abstract

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.