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ESWA
2007
146views more  ESWA 2007»
13 years 4 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...
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
13 years 8 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
BMCBI
2010
151views more  BMCBI 2010»
13 years 4 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
HICSS
2006
IEEE
97views Biometrics» more  HICSS 2006»
13 years 10 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...
CEC
2007
IEEE
13 years 8 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...