What are Precision & Recall in Machine Learning?
Precision and recall are commonly used metrics to measure the performance of machine learning models or AI solutions in general. It helps understand how well models are making predictions.
Let’s use an email SPAM prediction example. Say you have a model that looks at an email and decides whether it’s SPAM or NOT SPAM. To see how well it’s doing, you want to compare it with human-generated labels, which we will call the actual labels.
To demonstrate this, the table below shows you some actual labels and the machine (model) predicted labels. Now we’ll assume that the spam prediction is positive, and the not spam prediction