Python Machine Learning Cookbook - Second Edition

Getting ready

Polynomial models should be applied where the relationship between response and explanatory variables is curvilinear. Sometimes, polynomial models can also be used to model a non-linear relationship in a small range of explanatory variable. A polynomial quadratic (squared) or cubic (cubed) term converts a linear regression model into a polynomial curve. However, since it is the explanatory variable that is squared or cubed and not the beta coefficient, it is still considered as a linear model. This makes it a simple and easy way to model curves, without needing to create big non-linear models. Let's consider the following diagram:

We can see that there is a natural curve to the pattern of data points. This linear model is unable ...