Problem Five: (40 points) Consider the following data set comprised of three binary input attributes ( A1,A1, and A1) and one binary output (Y). a) What is the number of possible combinations? b) Use the decision trees learning algorithm to train a classification decision tree for the 5 examples. Show the computations made to determine the attribute to split at each node. c) Test the performance of the trained decision tree (determine P ). What is the percentage of correct matches