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» Confidence Intervals for the Area Under the ROC Curve
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ICPR
2006
IEEE
14 years 6 months ago
Rule Extraction from Support Vector Machines: Measuring the Explanation Capability Using the Area under the ROC Curve
Recently, the area of rule extraction from support vector machines (SVMs) has been explored. One important indication of the success of a rule extraction method is the performance...
Andrew P. Bradley, Nahla H. Barakat
ICPR
2006
IEEE
14 years 6 months ago
Linear model combining by optimizing the Area under the ROC curve
In some classification problems, like the detection of illnesses in patients, classes are very unbalanced and the misclassification costs for different classes vary significantly....
David M. J. Tax, Robert P. W. Duin
BMCBI
2010
126views more  BMCBI 2010»
13 years 5 months ago
A boosting method for maximizing the partial area under the ROC curve
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Osamu Komori, Shinto Eguchi
ICML
2004
IEEE
13 years 10 months ago
Optimising area under the ROC curve using gradient descent
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
Alan Herschtal, Bhavani Raskutti
SDM
2007
SIAM
130views Data Mining» more  SDM 2007»
13 years 6 months ago
Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets
Decision lists (or ordered rule sets) have two attractive properties compared to unordered rule sets: they require a simpler classification procedure and they allow for a more co...
Henrik Boström