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» Confidence Intervals for the Area Under the ROC Curve
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JMLR
2010
121views more  JMLR 2010»
13 years 2 months ago
A comparison of AUC estimators in small-sample studies
Reliable estimation of the classification performance of learned predictive models is difficult, when working in the small sample setting. When dealing with biological data it is ...
Antti Airola, Tapio Pahikkala, Willem Waegeman, Be...
BMCBI
2006
200views more  BMCBI 2006»
13 years 7 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
TMI
2002
191views more  TMI 2002»
13 years 7 months ago
Automatic Detection of Abnormalities in Chest Radiographs Using Local Texture Analysis
A fully automatic method is presented to detect abnormalities in frontal chest radiographs which are aggregated into an overall abnormality score. The method is aimed at finding ab...
Bram van Ginneken, Shigehiko Katsuragawa, Bart M. ...
IJPRAI
2010
151views more  IJPRAI 2010»
13 years 6 months ago
Structure-Embedded AUC-SVM
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...
Yunyun Wang, Songcan Chen, Hui Xue
IJON
2010
148views more  IJON 2010»
13 years 6 months ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...