The following data set will be used to learn a decision tree for predicting whether a mushroom is edible or not based on its shape, color, and odor. Shape C D D C D C C C D Color BB W W B B G U B W W Odor 1 1 1 2 2 22233 3 Edible Yes Yes Yes Yes Yes No No No No No No (a) What is entropy H(Edible Odor = 1 or Odor = 3)? (b) Which attribute would the C4.5 algorithm choose to use for the root of the tree? (c) Draw the full decision tree that would be learned for this data (no pruning). (d) Suppose we have a validation set as follows. What will be the training set error and validation set error of the tree? Express your answer as the number of examples that would be misclassified.