$($a$)$ Bank X has launched a new credit card with good benefits. The applicants need to satisfy certain criteria to be approved for this credit card. The features that are of interest to the bank are the customers$$ annual income, their credit score and if they are existing customers. The below Table shows some applications with their outcome.

Application ID Existing Customer Annual Income $()$ Credit Score Approved

$534$ yes $32000600$ no

$1378$ no $48352850$ yes

$5111$ no $18352350$ no

$17239$ yes $82476950$ yes

$19516$ yes $62591900$ no

$21321$ no $122591540$ yes

$27210$ yes $2591840$ yes

$56453$ no $77779980$ yes

$1517239$ yes $44445735$ no

$1723579$ no $29557432$ yes

$1912346$ yes $30112611$ no

$2224812$ no $82221711$ yes

The below Figure shows the decision tree created by training a model on credit card application data that are not available in the above Table.

$($i$)$ Obtain the predicted outcome for each application recorded in Table $1$ using this decision tree

$($ii$)$ Draw the confusion matrix for this task.

$($iii$)$ Calculate the accuracy, recall, precision and F$1$ score.