Rf

In this class, we will introduce Random Forest as a new boosting machine algorithm using randomness in two ways to incrementally add trees:

• By sub-sampling a random training set in the original training set as in bagging methods.
• By selecting a random subset of features on which performing tree splits for each choice of split.

The method is then showcased in simple classification tasks.

Notebook

References

• Wikipedia page on Random Forest

• Random Forests. Breiman, Leo, Machine learning 45.1 (2001): 5-32.

• Understanding random forests: From theory to practice. Louppe, Gilles, PhD thesis.