QUESTIONS ONE:

A classification model produced $79$ True Positives $($TP$),101$ False Negatives $($FN$),1294$

True Negatives $($TN$)$ and $15$ False Positives $($FP$)$ on a test set when trained using a dataset

with similar distribution.

i$.$ Construct the confusion matrix table.

ii$.$ Use the above information to compute the classification accuracy of the model. Based

on the computed accuracy, is it worth concluding that the model generalised well on

the test set?

$[10$ marks$]$

iii. Compute the recall and precision and explain their representation of the model's

performance and suggest possible trade$-$offs if necessary.

$[10$ marks$]$

TOTAL MARKS $[30$ marks$]$