Definition: You are given a question on machine learning. You are also given 4 answer options (associated with "A", "B", "C", "D"), out of which only one is correct. You need to answer the question by selecting the correct option. You should only answer with the choice letter, not the whole answer.
Input: Which of the following is/are true regarding an SVM?
(A)For two dimensional data points, the separating hyperplane learnt by a linear SVM will be a straight line. (B)In theory, a Gaussian kernel SVM cannot model any complex separating hyperplane. (C)For every kernel function used in a SVM, one can obtain an equivalent closed form basis expansion. (D)Overfitting in an SVM is not a function of number of support vectors.
