64. Precision and Recall: Beyond Accuracy

Last post you saw that accuracy can be 95% while your model catches zero fraud. Precision and recall are the fix. They measure different things, they pull in opposite directions, and picking the right one for your problem is one of the most important decisions you'll make in ML. Most people know the definitions but don't know when to use which one. That's what this post is really about. What You'll Learn Here Precision and recall in plain words with real examples Why improving one usually hurts