Supervised Learning

Supervised learning is a learning system that trains using labeled data (data in which the target variables are already known). The model learns how patterns in the feature matrix map to the target variables. When the trained machine is fed with a new dataset, it can use what it has learned to predict the target variables. This can also be called predictive modeling.

Supervised learning is broadly split into two categories. These categories are as follows:

Classification mainly deals with categorical target variables. A classification algorithm helps to predict which group or class a data point belongs to.

When the prediction is between two classes, it is known as binary classification. An example is predicting whether or not a customer will buy a product (in this case, the classes are yes and no).

If the prediction involves more than two target classes, it is known as multi-classification; for example, predicting all the items that a customer...