a.1) Why are Decision Tree classifiers so popular? What is the purpose of Tree Pruning?

a.2) How is Gini Index used in CART? How does it deal with discrete-valued and continuous-valued attribute?

a.3) Decision trees can suffer from Repetition and Replication, making them overwhelming to interpret. what are those? How can we solve those problems?

a.4) Given a decision tree, you have the option of (i) converting the decision tree to rules and then pruning the resulting rules, or (ii) pruning the decision tree and then converting the pruned tree to rules. What advantage does (i) have over (ii)?

(5 + 10 + 10 + 5 Marks)