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» An Empirical Evaluation of Supervised Learning for ROC Area
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ROCAI
2004
Springer
13 years 10 months ago
An Empirical Evaluation of Supervised Learning for ROC Area
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
Rich Caruana, Alexandru Niculescu-Mizil
NIPS
2004
13 years 6 months ago
A Large Deviation Bound for the Area Under the ROC Curve
The area under the ROC curve (AUC) has been advocated as an evaluation criterion for the bipartite ranking problem. We study large deviation properties of the AUC; in particular, ...
Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan...
ICML
2005
IEEE
14 years 5 months ago
ROC confidence bands: an empirical evaluation
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...
Sofus A. Macskassy, Foster J. Provost, Saharon Ros...
IBPRIA
2009
Springer
13 years 9 months ago
Score Fusion by Maximizing the Area under the ROC Curve
Information fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the paramete...
Mauricio Villegas, Roberto Paredes
ROCAI
2004
Springer
13 years 10 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...