Define precision and recall?

Perfection is defined as the percentage of applicable instances among all recovered instances. Recall also called "sensitivity", is the percentage of instances retrieved from all relevant instances. An ideal classifier has both precisions and recalls equivalent to 1.

Note: The purpose of the ML design interview is to transform the data and identify important patterns or gain key insights from the data.