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

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