* 7. The following table lists a dataset collected in an electronics shop showing details of customers and whether they responded to a special offer to buy a new laptop. AGE INCOME STUDENT CREDIT BUYS no bad no no high high high med low low low good bad bad yes yes yes no 40 > 40 > 40 31 - 40 40 40 yes yes yes no yes yes yes no med low bad good good bad good bad good good bad good yes yes yes med med med high med yes no yes yes 14 no yes no This dataset has been used to build a decision tree to predict which cus- tomers will respond to future special offers. The decision tree, created using the ID3 algorithm, is shown below. AGE 40 CREDIT STUDENT yes AL bad good no yes yes no no yes a. The information gain (calculated using entropy) of the feature AGE at the root node of the tree is 0.247. A colleague has suggested that the STUDENT feature would be better at the root node of the tree. Show that this is not the case. b. Yet another colleague has suggested that the ID feature would be a very effective at the root node of the tree. Would you agree with this suze tion