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• W2206560168 abstract "Cost curves have recently been introduced as an alternative or complement to ROC curves in order to visualize binary classifiers performance. Of importance to both cost and ROC curves is the computation of confidence intervals along with the curves themselves so that the reliability of a classifier's performance can be assessed. Computing confidence intervals for the difference in performance between two classifiers allows the determination of whether one classifier performs significantly better than another. A simple procedure to obtain confidence intervals for costs or the difference between two costs, under various operating conditions, is to perform bootstrap resampling of the test set. In this paper, we derive exact bootstrap distributions for these values and use these dstributions to obtain confidence intervals, under various operating conditions. Performances of these confidence intervals are measured in terms of coverage accuracies. Simulations show excellent results." @default.
• W2206560168 created "2016-06-24" @default.
• W2206560168 creator A5030282213 @default.
• W2206560168 creator A5068850091 @default.
• W2206560168 date "2008-01-01" @default.
• W2206560168 modified "2023-10-02" @default.
• W2206560168 title "Pointwise exact bootstrap distributions of cost curves" @default.
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• W2206560168 doi "https://doi.org/10.1145/1390156.1390192" @default.
• W2206560168 hasPublicationYear "2008" @default.
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