$($a$)$ The "Telco Customer Churn" dataset contains information about customers of a telecommunications company. The goal is to predict whether a customer will churn $($leave$)$ the service based on various features outlined below:

Churn $($no$,$ yes$)$

gender $($Female$,$ Male$)$

Dependents $($no$,$ yes$)$

PaperlessBilling $($no$,$ yes$)$

MonthlyCharges $($in dollars$)$

TechSupport $($no$,$ yes$)$

InternetService $("$DSL$",$ "Fiber optic", $"$No$")$

The classification tree is shown below:

i$.$ Replace A and $B$ in the code below that fits the classification tree model to the churn$\_$dat and creates the classification tree as shown above $[4$ marks$]$

fit$\_$tree A$]($Churn $..$ data $=$ churn$\_$data$)$ rpart.plot$([$B$])$