Imagine you are working on a data science project to build a classification algorithm. You trained

a classifier on the training dataset and thereafter obtained the following confusion matrix on test

dataset. Interpret the confusion matrix and calculate classifier$$s performance $($using recall and

precision$)$ to summarize how well the algorithm has performed.

Predicted NO Predicted YES

Actual NO $5812$

Actual YES $991$