Problem 1 (20 points): The following table consists of training data from an employee database. The data have been generalized. For example, "31... 35" for age represents the age category with 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 department status age sales Sales sales systems systems systems systems marKetingSenior marketing junior 31...35 41K... 45K4 secretary secretary salary count senior 31...35 46K.. . 50K 30 junior 26...30 26K... 30K 40 junior 31...3531K... 35K 40 junior 21... 2546K...50K 20 senior 31...35 66K... 70K 5 junior 26...30 46K...50K 3 senior 41...45 66K... 70K 3 36. ..40 46K.. . 50K 10 senior 46. ..50 36K... 40K4 junior 26...30 26K...30K 6 Let status be the class label attribute. (a) Construct a decision tree from the given data using information gain. Use R to verify your result and show your code. (b) Given a data tuple having the values "systems", "31... 35", and "46K-50K" for the attributes department, age, and salary, respectively, what would a naive Bayesian classification of the status for the tuple be? Problem 1 (20 points): The following table consists of training data from an employee database. The data have been generalized. For example, "31... 35" for age represents the age category with 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 department status age sales Sales sales systems systems systems systems marKetingSenior marketing junior 31...35 41K... 45K4 secretary secretary salary count senior 31...35 46K.. . 50K 30 junior 26...30 26K... 30K 40 junior 31...3531K... 35K 40 junior 21... 2546K...50K 20 senior 31...35 66K... 70K 5 junior 26...30 46K...50K 3 senior 41...45 66K... 70K 3 36. ..40 46K.. . 50K 10 senior 46. ..50 36K... 40K4 junior 26...30 26K...30K 6 Let status be the class label attribute. (a) Construct a decision tree from the given data using information gain. Use R to verify your result and show your code. (b) Given a data tuple having the values "systems", "31... 35", and "46K-50K" for the attributes department, age, and salary, respectively, what would a naive Bayesian classification of the status for the tuple be