Supervised Learning

There are two major types of supervised machine learning problems, called classification and regression.

In classification, the goal is to predict a class label, which is a choice from a predefined list of possibilities. Classification is sometimes separated into binary classification, which is the special case of distinguishing between exactly two classes, and multiclass classification, which is classification between more than two classes.

For regression tasks, the goal is to predict a continuous number, or a floating-point number in programming terms (or real number in mathematical terms). Predicting a person’s annual income from their education, their age, and where they live is an example of a regression task.