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» Optimal feature selection for support vector machines
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ESANN
2006
13 years 9 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...
WADS
2001
Springer
80views Algorithms» more  WADS 2001»
14 years 3 days ago
Optimization over Zonotopes and Training Support Vector Machines
Marshall W. Bern, David Eppstein
ESANN
2004
13 years 9 months ago
On-line support vector machines and optimization strategies
Juan Manuel Górriz, Carlos García Pu...
IJCNN
2000
IEEE
14 years 2 days ago
Optimization on Support Vector Machines
João Pedro Pedroso, Noboru Murata
ICML
2007
IEEE
14 years 8 months ago
Hybrid huberized support vector machines for microarray classification
The large number of genes and the relatively small number of samples are typical characteristics for microarray data. These characteristics pose challenges for both sample classif...
Li Wang, Ji Zhu, Hui Zou