$($a$)$ How would you modify the basic decision tree algorithm to take into

consideration the count of each generalized data tuple $($i$.$e$.,$ of each row entry$)?$

$($b$)$ Use your algorithm to construct a decision free from the given data.

$($c$)$ Given a data tuple having value $$marketing$,26..\mathrm{.}30,$ and $46-50$K$$ for the

attributes department, age and salary, respectively, what would your decision tree

classification of the status for the tuple be$?$

$($d$)$ Given a data tuple having value $$marketing$,26..\mathrm{.}30,$ and $46-50$K$$ for the

attributes department, age and salary, respectively, what would a na$$ve Bayesian

classification of the status for the tuple be