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» An SMO Algorithm for the Potential Support Vector Machine
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ICIC
2005
Springer
13 years 11 months ago
Methods of Decreasing the Number of Support Vectors via k-Mean Clustering
This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
CEC
2007
IEEE
13 years 12 months ago
Concerning the potential of evolutionary support vector machines
— Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the cl...
Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumi...
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
14 years 8 days ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
CANDC
2002
ACM
13 years 5 months ago
Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis
We show that the support vector machine (SVM) classification algorithm, a recent development from the machine learning community, proves its potential for structure
Robert Burbidge, Matthew W. B. Trotter, Bernard F....
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
13 years 11 months ago
Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression
We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. B...
Shirish Krishnaj Shevade, Wei Chu