Question: What is the purpose of the term 'precision' in binary classification?

Answer: Precision is a metric that measures the accuracy of positive predictions made by a model. It is the ratio of true positive predictions to the sum of true positives and false positives.

Example:

In fraud detection, precision is crucial to minimize the number of false positives, i.e., legitimate transactions flagged as fraudulent.