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JISE
2010
144views more  JISE 2010»
13 years 2 days 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
GRC
2008
IEEE
13 years 6 months ago
Adaptive and Iterative Least Squares Support Vector Regression based on Quadratic Renyi Entropy
An adaptive and iterative LSSVR algorithm based on quadratic Renyi entropy is presented in this paper. LS-SVM loses the sparseness of support vector which is one of the important ...
Jingqing Jiang, Chuyi Song, Haiyan Zhao, Chunguo W...
ISNN
2005
Springer
13 years 10 months ago
Support Vector Regression for Software Reliability Growth Modeling and Prediction
In this work, we propose to apply support vector regression (SVR) to build software reliability growth model (SRGM). SRGM is an important aspect in software reliability engineering...
Fei Xing, Ping Guo
BMCBI
2007
139views more  BMCBI 2007»
13 years 5 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
OL
2007
103views more  OL 2007»
13 years 4 months ago
Support vector machine via nonlinear rescaling method
In this paper we construct the linear support vector machine (SVM) based on the nonlinear rescaling (NR) methodology (see [9, 11, 10] and references therein). The formulation of t...
Roman A. Polyak, Shen-Shyang Ho, Igor Griva