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» Optimizing Area Under Roc Curve with SVMs
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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 Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
ICDM
2006
IEEE
182views Data Mining» more  ICDM 2006»
13 years 11 months ago
Active Learning to Maximize Area Under the ROC Curve
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Matt Culver, Kun Deng, Stephen D. Scott
BMCBI
2007
132views more  BMCBI 2007»
13 years 5 months ago
On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve
Background: Novel molecular and statistical methods are in rising demand for disease diagnosis and prognosis with the help of recent advanced biotechnology. High-resolution mass s...
Jingjing Ye, Hao Liu, Crystal Kirmiz, Carlito B. L...
IJCNN
2006
IEEE
13 years 11 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang