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 Play Tennis No No Yes Rain Yes Temp. Humidity Hot High Hot High Hot High Mild High Cool Normal Cool Normal Cold Normal Mild Normal Mild Normal Mild High Hot Normal Mild High Rain Overcast Sunny Rain Sunny Overcast Overcast Rain Wind Weak Strong Weak Weak Strong Weak Weak Strong Strong Strong Weak Strong No Yes Yes Yes Yes Yes Yes No 1. [10 Points] Calculate the information gain for the four attributes. 2. [5 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? =