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» Optimization on Support Vector Machines
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ICML
2010
IEEE
15 years 7 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»
15 years 6 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»
16 years 9 days 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
16 years 7 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 10 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...