1) Consider the training data samples shown in the table below for a binary classification problem. Instance Target Class a1 02 1234 T T 1.0 2 T T 6.0 + 3 T F 5.0 4 F F 4.0 5 F T 7.0 6 F T 3.0 F F 8.0 T F 7.0 9 F T 5.0 a. The formula of entropy is given by: Entropy(t)p(it) log, p(it), Where c is the number of classes and p(j/t) is the relative frequency of class j at node t. What is the entropy of this collection of training examples with respect to the positive class? b. What are the information gains of a1 and A2 relative to these training data samples? C. For as, which is a continuous attribute, compute the information gain for every possible split.