Given a training set of 10 million tuples with 10 attributes each taking 8 bytes space. One attribute is a class label with two distinct values, whereas for other attributes each has 50 distinct values. Assume your machine cannot hold all the dataset in the main memory. Outline an efficient method that constructs Naive Bayes classifier efficiently, and answer the following questions explicitly:how many scans of the database does your algorithm take?Answer:(ii) what is the maximum memory space your algorithm will use in your induction?Answer:
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