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» Infinite Ensemble Learning with Support Vector Machines
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SMC
2007
IEEE
156views Control Systems» more  SMC 2007»
15 years 8 months ago
Dynamic fusion of classifiers for fault diagnosis
—This paper considers the problem of temporally fusing classifier outputs to improve the overall diagnostic classification accuracy in safety-critical systems. Here, we discuss d...
Satnam Singh, Kihoon Choi, Anuradha Kodali, Krishn...
BMCBI
2010
190views more  BMCBI 2010»
15 years 2 months ago
APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility
Background: It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understandin...
Jun-Feng Xia, Xing-Ming Zhao, Jiangning Song, De-S...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 2 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
ICML
2007
IEEE
16 years 2 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
161
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ESANN
2006
15 years 3 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...