Multiple Linear Regression

Multiple Linear Regression is Linear Regression with more than one input variable. The model predicts the output as a weighted sum of the features plus a bias:

$\hat{y} = w_1x_1 + w_2x_2 + \dots + w_nx_n + b$

Each weight describes how much the prediction changes when its feature increases by one, holding the other features constant.

See Linear Regression.