Regression

Regression deals with learning continuous mapping functions that can predict values provided by various input features. The function can be linear or non-linear. If the function is linear, it is referred to as linear regression, and if it is non-linear, it is commonly called polynomial regression. Predicting values when there are multiple input features (variables), we call multi-variate regression. A very typical example of regression is the house prediction problem. Provided with the various parameters of a house, such as build area, locality, number of rooms, and so on, the accurate selling price of the house can be predicted using historic data.