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Abstract: This paper is about constructing confidence bands around ROC curves. We first introduce to the machine learning community three band-generating methods from the medical field, and evaluate how well they perform. Such confidence bands represent the region where the "true" ROC curve is expected to reside, with the designated confidence level. To assess the containment of the bands we begin with a synthetic world where we know the true ROC curve---specifically, where the class-conditional model... (Update)
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BibTeX entry: (Update)
Macskassy, S., Provost, F., & Rosset, S. (2005). ROC Confidence Bands: An Empirical Evaluation. Proceedings of the 22nd International Conference on Machine Learning (ICML). Bonn, Germany. http://citeseer.ist.psu.edu/macskassy05roc.html More
@misc{ macskassy05roc,
author = "S. Macskassy and F. Provost and S. Rosset",
title = "ROC Confidence Bands: An Empirical Evaluation",
text = "Macskassy, S., Provost, F., & Rosset, S. (2005). ROC Confidence Bands:
An Empirical Evaluation. Proceedings of the 22nd International Conference
on Machine Learning (ICML). Bonn, Germany.",
year = "2005",
url = "citeseer.ist.psu.edu/macskassy05roc.html" }
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