In this chapter you will learn about another supervised machine learning algorithm - Multiple Linear Regression
In multiple Linear Regression we have more than one feature to predict the target. Here the equation for the best fit line is a bit modified and is :
Where :-
X1,x2,x3,..,xn are the independent variables or features
Y is the response to the independent variable
B0,B1,B2,B3,....Bn are the corresponding coefficients of the independent variables
E is the random error obtained along with the predicted value.
The code:-