An SVM is trained with the following data a) Using a Linear kernel, what is the optimization problem that needs to be solved to determine the support vectors. b) Assume that the Lagrangian coefficients for the optimization problem have the values, 1 = 1/8, 2-1/8, a3-0 What the data points are the support vectors? Given a new instance (-1,0), how does the SVM classify this? An SVM is trained with the following data a) Using a Linear kernel, what is the optimization problem that needs to be solved to determine the support vectors. b) Assume that the Lagrangian coefficients for the optimization problem have the values, 1 = 1/8, 2-1/8, a3-0 What the data points are the support vectors? Given a new instance (-1,0), how does the SVM classify this