scikit-learn : Machine Learning Simplified

Polynomial regression

In the previous examples, we assumed that the real relationship between the explanatory variables and the response variable is linear. This assumption is not always true. In this section, we will use polynomial regression, a special case of multiple linear regression that adds terms with degrees greater than one to the model. The real-world curvilinear relationship is captured when you transform the training data by adding polynomial terms, which are then fit in the same manner as in multiple linear regression. For ease of visualization, we will again use only one explanatory variable, the pizza's diameter. Let's compare linear regression with polynomial regression using the following datasets:

Training Instance	Diameter ...