Upper and Lower Bounds of Area Under ROC Curves and Index of Discriminability of Classifier Performance
نویسندگان
چکیده
Area under an ROC curve plays an important role in estimating discrimination performance – a well-known theorem by Green (1964) states that ROC area equals the percentage of correct in two-alternative forcedchoice setting. When only single data point is available, the upper and lower bound of discrimination performance can be constructed based on the maximum and minimum area of legitimate ROC curves constrained to pass through that data point. This position paper, after reviewing a property of ROC curves parameterized by the likelihood-ratio, presents our recently derived formula of estimating such bounds (Zhang & Mueller, 2005).
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