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Extensive Guide to Support Vector Machines - inovex GmbH

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Support vector machines (SVMs) are supervised machine learning models. They are the most prominent member of the class of kernel methods. SVMs can be used both for classification and regression. The original SVM proposed in 1963 is a simple binary linear classifier. Special to SVMs is that they use not any hyperplane but the one that maximizes the distance between itself and the two sets of datapoints.