Question: a$)$Assume six data points with two binary attributes, x$1$and x$2,$are given as listed in Table $1.$These data points belong to three classes, Yin$\{1,2,3\},$and our purpose is to classify these datapoints using a decision tree classifier with only one split.i$.$Calculate the information gain values when the datapoints are split using x$1$and x$2\mathrm{.}30\%$ii$.$ a $)$Assume six data points with two binary attributes, $1$and $2,$are given as listed in Table $1.$These data points belong to three classes, Yin $\{1,2,3\},$and our purpose is to classify these datapoints using a decision tree classifier with only one split. i $.$Calculate the information gain values when the datapoints are split using $1$and $2.30\%$ ii $.$Explain which split is better and why. Draw the decision tree using the best split, label the branches, and determine what the predicted class label is in each leaf. $[10\%]$ Table $1.$