Given a training set of 50 million tuples with 25 attributes each taking 4 bytes space. One attribute is a class label with two distinct values, whereas for other attributes each has 30 distinct values. You have only a 512 MB main memory laptop. Outline an efficient method that constructs decision trees efficiently, and answer the following questions explicitly:
(1) How many scans of the database does your algorithm take if the maximal depth of decision tree derived is 5?
(2) What is the maximum memory space your algorithm will use in your tree induction?