Please answer in 1 hour, thanks

(a) Support vector machines learn a decision boundary leading to the largest margin from both classes. You are training SVM on a tiny dataset with 4 points shown in the following figure. This dataset consists of two examples with class label -1 (denoted with plus), and two examples with class label +1 (denoted with triangles). What's the equation corresponding to the decision boundary for this Hard Margin SVM? (4 points) (b) Circle the support vectors and draw the decision boundary. (2 points) (c) For the given prediction results, please calculate Precision, Recall, TPR, and F-measure. (4 points) ACTUAL CLASS Class Yes Class=No 40 40 PREDICTED Class=Yes CLASS Class=No 10 10 (a) Support vector machines learn a decision boundary leading to the largest margin from both classes. You are training SVM on a tiny dataset with 4 points shown in the following figure. This dataset consists of two examples with class label -1 (denoted with plus), and two examples with class label +1 (denoted with triangles). What's the equation corresponding to the decision boundary for this Hard Margin SVM? (4 points) (b) Circle the support vectors and draw the decision boundary. (2 points) (c) For the given prediction results, please calculate Precision, Recall, TPR, and F-measure. (4 points) ACTUAL CLASS Class Yes Class=No 40 40 PREDICTED Class=Yes CLASS Class=No 10 10