Main take-away

Wrap-up

In this module, we presented decision trees in details. We saw that they:

• are suited for both regression and classification problems;

• are non-parametric models;

• are not able to extrapolate;

• are sensitive to hyperparameter tuning.

To go further

You can refer to the following scikit-learn examples which are related to the concepts approached during this module:

• Example of decision tree regressor

• Example of decision tree classifier

• Understanding the tree structure in scikit-learn

• Post-pruning decision trees