The following table consists of training data from an employee database, where department, age, and salary are attributes, and status is the class label. 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 | 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 |
Using NB classifier, predict the class label for an employee having the values "systems", "31...35", and "46K...50K" for attributes department, age, and salary.
