Hong-da Zhang, Xiao-dan Wang, Hai-long Xu, Yan-lei Li, Wen Quan
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To improve the training speed of SVM, we propose a new SVM training approach which takes thick convex-hull as training set. The approach makes better use of the margin information for classification of data sets, and thus extends the use of convex hull to approximately linearly separable problems. Experiments on 5 UCI data sets indicate that the approach speeds up training of SVM with guarantee of generalization accuracy.
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