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» Optimization on Support Vector Machines
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ICML
2010
IEEE
14 years 11 months ago
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification
We propose a novel approach that reduces cost-sensitive classification to one-sided regression. The approach stores the cost information in the regression labels and encodes the m...
Han-Hsing Tu, Hsuan-Tien Lin
CORR
2006
Springer
130views Education» more  CORR 2006»
14 years 10 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
HICSS
2006
IEEE
97views Biometrics» more  HICSS 2006»
15 years 4 months ago
Dynamically Optimizing Parameters in Support Vector Regression: An Application of Electricity Load Forecasting
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...
Chin-Chia Hsu, Chih-Hung Wu, Shih-Chien Chen, Kang...
ICML
2005
IEEE
15 years 10 months ago
Adapting two-class support vector classification methods to many class problems
A geometric construction is presented which is shown to be an effective tool for understanding and implementing multi-category support vector classification. It is demonstrated ho...
Simon I. Hill, Arnaud Doucet
CEC
2007
IEEE
15 years 1 months ago
Prediction of protein interactions by combining genetic algorithm with SVM method
This paper proposes a novel hybrid GA/SVM method that can predict the interactions between proteins intermediated by the protein-domain relations. Firstly, we represented a protein...
Bing Wang, Lu-Sheng Ge, Wen-You Jia, Li Liu, Fu-Ch...