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(self, X, y):\n", " m, n = X.shape\n", "\n", " # function to be minimized - the argument bw is a vector [b, w_1, ..., w_n]\n", " get_norm = lambda bw: 0.5 * np.sum(bw[1:] ** 2)\n", "\n", " # these constraints force all the training set to be ...