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JISE
2010
144views more  JISE 2010»
13 years 1 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 7 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
BMCBI
2010
159views more  BMCBI 2010»
13 years 6 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao
IWANN
2009
Springer
14 years 1 months ago
Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
ESWA
2007
146views more  ESWA 2007»
13 years 6 months ago
A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
Two parameters, C and r, must be carefully predetermined in establishing an efficient support vector machine (SVM) model. Therefore, the purpose of this study is to develop a gene...
Chih-Hung Wu, Gwo-Hshiung Tzeng, Yeong-Jia Goo, We...