Learn
Multiple Linear Regression
Review
Great work! Let’s review the concepts before you move on:
- Multiple Linear Regression uses two or more variables to make predictions about another variable:
- Multiple linear regression uses a set of independent variables and a dependent variable. It uses these variables to learn how to find optimal parameters. It takes a labeled dataset and learns from it. Once we confirm that it’s learned correctly, we can then use it to make predictions by plugging in new
x
values. - We can use scikit-learn’s
LinearRegression()
to perform multiple linear regression. - Residual Analysis is used to evaluate the regression model’s accuracy. In other words, it’s used to see if the model has learned the coefficients correctly.
- Scikit-learn’s
linear_model.LinearRegression
comes with a.score()
method that returns the coefficient of determination R² of the prediction. The best score is 1.0.
Instructions
We have made an applet using the multiple linear regression model that you built! Have fun!