(3) Decision Tree (6 marks) Suppose you are designing a DT classifier to processing the following data set: RID age no no no income student credit-rating Class: buys.computer 1 youth high fair no 2 youth high excellent no 3 middle-aged high fair yes 4 senior medium fair yes 5 senior low yes fair yes 6 senior low excellent 7 middle aged low yes excellent 8 youth medium no fair no 9 youth low fair 10 senior medium yes fair yes 11 youth excellent 12 middle-aged medium excellent yes 13 middle-aged high fair yes 14 senior medium no excellent no yes medium yes 00 Present the process of using InfoGain to split the data set according to the "student" feature. Detail the steps in your computation process. CSC/316 Page 1 of 3 (An answer template: 1. Step 1: before the split, the Shannon entropy is ii. Step 2: after the split , for the case "student=yes", the Shannon entropy is ; for the case "student=no", the Shannon entropy is iii. Step 3: the conditional Shannon entropy is and thus the InfoGain is )