The following data set-2 consists of training data from an employee database. The data have been generalized. For example, "31 ... 35 for age represents the age range of 31 to 35. For a given row entry, count represents the number of data tuples having the values for department, status, age, and salary given in that row, let status be the class label attribute. Data set S2: department status age salary count sales senior 31...35 46K...50K 30 sales junior 26...30 26K... 30K 40 sales junior 31...35 31K... 35K 40 systems junior 21... 25 46K...50K 20 systems senior 31...35 66K... 70K 5 systems junior 26...30 46K...50K 3 systems senior 41...45 66K... 70K 3 marketing senior 36...40 46K... 50K 10 marketing junior 31...35 41K...45K 4 secretary senior 46...50 36K... 40K 4 secretary junior 26...30 26K...30K 6 (a). Use ID3 algorithm to construct a decision tree for the data given in data set 2. (b). Given a data tuple having the values ("systems, 26...30", and "4650K) for the attributes department, age, and salary, respectively, what would a naive Bayesian classification(use data set-2) of the status for the tuple be