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