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» Score Fusion by Maximizing the Area under the ROC Curve
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IJCNN
2006
IEEE
13 years 11 months ago
Data Fusion for Outlier Detection through Pseudo-ROC Curves and Rank Distributions
— This paper proposes a novel method of fusing models for classification of unbalanced data. The unbalanced data contains a majority of healthy (negative) instances, and a minor...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
DATAMINE
2008
112views more  DATAMINE 2008»
13 years 5 months ago
PRIE: a system for generating rulelists to maximize ROC performance
Rules are commonly used for classification because they are modular, intelligible and easy to learn. Existing work in classification rule learning assumes the goal is to produce ca...
Tom Fawcett
ECML
2007
Springer
13 years 11 months ago
An Improved Model Selection Heuristic for AUC
Abstract. The area under the ROC curve (AUC) has been widely used to measure ranking performance for binary classification tasks. AUC only employs the classifier’s scores to ra...
Shaomin Wu, Peter A. Flach, Cèsar Ferri Ram...
IPMU
2010
Springer
13 years 3 months ago
Performance Comparison of Fusion Operators in Bimodal Remote Sensing Snow Detection
Abstract. This contribution describes the system developed and implemented for the detection of snow based on the fusion of optical and Synthetic Aperture Radar (SAR) remote sensin...
Aureli Soria-Frisch, Antonio Repucci, Laura Moreno...
SDM
2012
SIAM
234views Data Mining» more  SDM 2012»
11 years 7 months ago
On Evaluation of Outlier Rankings and Outlier Scores
Outlier detection research is currently focusing on the development of new methods and on improving the computation time for these methods. Evaluation however is rather heuristic,...
Erich Schubert, Remigius Wojdanowski, Arthur Zimek...