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» Optimizing Area Under Roc Curve with SVMs
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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
BMCBI
2010
150views more  BMCBI 2010»
13 years 7 months ago
AMS 3.0: prediction of post-translational modifications
Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, us...
Subhadip Basu, Dariusz Plewczynski
CIMAGING
2010
122views Hardware» more  CIMAGING 2010»
13 years 9 months ago
Symmetrized local co-registration optimization for anomalous change detection
The goal of anomalous change detection (ACD) is to identify what unusual changes have occurred in a scene, based on two images of the scene taken at different times and under diff...
Brendt Wohlberg, James Theiler
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
JAIR
2002
95views more  JAIR 2002»
13 years 7 months ago
SMOTE: Synthetic Minority Over-sampling Technique
An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally repres...
Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hal...