An Analysis of Reliable Classifiers through ROC Isometrics
نویسندگان
چکیده
Reliable classifiers abstain from uncertain instance classifications. In this paper we extend our previous approach to construct reliable classifiers which is based on isometrics in Receiver Operator Characteristic (ROC) space. We analyze the conditions to obtain a reliable classifier with higher performance than previously possible. Our results show that the approach is generally applicable to boost performance on each class simultaneously. Moreover, the approach is able to construct a classifier with at least a desired performance per class.
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تاریخ انتشار 2006