Question II: Decision Tree-Classifier (40 points) Suppose we are given, the dataset listed in table below for a classification problem. There are four input attributes. We learn a decision tree classifier. Outlook Sunny Sunny Overcast Rain Rain Overcast Sunny Rain Sunny Overcast Overcast Rain Temp. Humidity Humidity Wind Hot High Weak Hot High Strong Hot High Weak Mild High Weak Cool Normal Strong Cool Normal Weak Cold Normal Weak Mild Normal Strong Mild Normal Strong Mild High Strong Hot Normal Weak Mild High Strong Play Tennis No No Yes Yes No Yes Yes Yes Yes Yes Yes No 1. [10 Points) Calculate the information gain for the four attributes. 2. 15 Points, Which attribute is used for the first split at the root node of the tree? Justify? 3. [20 Points) Draw the decision tree resulting from using this split alone. Show all your steps, work and calculation. Make sure to label the split attribute, the corresponding branches and the predicted label of each leaf. 4. [5 Points) How would this tree classify an example with Outlook = Rain, Temp = Hot, Humidity = Normal, and Wind = weak? Justify