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In this paper, we propose a novel online learning classification algorithm, which is based on support vector machine (SVM) and approximate convex hull vertices selection. Considering the geometrical features of SVM, we can safely delete the samples inside the convex hulls. However, in general, if the dimension of the training data is high, most of the samples are the convex hull vertices and therefore...
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