2. Consider the following set of training data for a binary classification problem: Gender Class CO M M Shirt Size Small Medium Medium Large Extra Large Extra Large Small Small Medium CO CO CO CO CO CO CO Car Type Family Sports Sports Sports Sports Sports Sports Sports Sports Luxury Family Family Family Luxury Luxury Luxury Luxury Luxury Luxury Luxury Lunge M EDHE C1 M ci CI Large Extra Large Medium Extra Large Small Small Medium Medium Medium Large CI C1 F F 20 E C1 (a) Compute the weighted average Gini index for the overall collection of training data (ie, the parent node). (b) Compute the weighted average Gini index for the Gender attribute. (c) Compute the weighted average Gini index for the Car Type attribute using multiway split (as opposed to one of the binary splits). (d) Compute the weighted average Gini index for the Shirt Size attribute using multiway split. (e) Which attribute is better to use as the first split in a decision tree? (f) Now compute the weighted average Gini index for the Customer ID attribute. Why should this not be used as an attribute test condition