Suppose we generate a training set from a decision tree andthen apply decision-tree learning to that training set. is it thecase that the learning algorithm will eventually return thecorrect tree as the training set size goes to infinity? why orwhy not?

Write a function so that the main program below can be replaced by the simpler code that calls function original main program: miles_per_hour = float( minutes_traveled = float( hours_traveled = minutes_traveled / 60.0 miles_traveled = hours_traveled * miles_per_hour print('miles: %f' % miles_traveled) sample output with inputs: 70.0 100.0 miles: 116.666667

What is the first view you place in your drawing?

Companies that implement and apply an information system effectively can create