Regression trees

You have learned how trees are used in order to classify a prediction as belonging to a particular class or category. However, trees can also be used to solve problems related to predicting numeric outcomes. In this section, you will learn about the three types of tree based algorithms that you can implement in scikit-learn in order to predict numeric outcomes, instead of classes:

• The decision tree regressor
• The random forest regressor
• The gradient boosted tree

The decision tree regressor

When we have data that is non-linear in nature, a linear regression model might not be the best model to choose. In such situations, it makes sense to choose a model that can fully capture the non-linearity of such data...