A binary classification task with input vectors X, and targets tn E{ +1, - 1} is perfectly achieved by a support vector machine classifier )(x) = wif(x) + b. where f(x) are feature vectors. The weight vector that achieves 1/2 1/3 this is w = (-6., 6.) and (-3.0,-4.5) are support vectors. Identify all the statements that are correct. A. (-6., 6.) is a support vector belonging to class +1 and (-3.0,-4.5) is a support vector belonging to class - 1. OB. The Euclidean distance between support vectors (-6., 6.) and (-3.0,-4.5) is greater than twice the distance of either point to the decision boundary. C. A test point (2.-7) is predicted to be in class -1. D. The distance from either support vector to the decision boundary is 1.66 E. (-6., 6.) is a support vector belonging to class -1 and (-3.0,-4.5) is a support vector belonging to class +1. OF. A test point (2, -7) is predicted to be in class +1