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Support Vector Machines, presented for the problem of identifying two groups of points on the plane

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In terms of ideas, SVM uses tricks to map the original dataset to more dimensional spaces. Once mapped to a multidimensional space, SVM will review and select the most suitable superlattice to classify that data set. | Support Vector Machines, presented for the problem of identifying two groups of points on the plane

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