- PART I: Consider the following training dataset and the original decision tree induction algorithm(ID3). Risk is the class label attribute. The height values have been already discretized into distinct ranges. Calculate the information gain if height is chosen as the test attribute. Draw the final decision tree without any pruning for the training dataset. Generate all the "IF-THEN" rules from the decision tree. GENDER HEIGHT RISK F {1.5, 1.6} Low M {1.9, 2.0} High F {1.8, 1.9} Medium F {1.8, 1.9} Medium F {1.6, 1.7} Low M {1.8, 1.9} Medium F {1.5, 1.6} Low M {1.6, 1.7} Low M (2.0, co} High M (2.0, co} High F {1.7, 1.8} Medium M {1.9, 2.0} Medium F {1.8, 1.9} Medium F {1.7, 1.8} Medium F {1.7, 1.8} Medium