4. Decision trees

Decision trees

Learning Process

Decision tree learning

Measuring purity

Choosing a split: Information Gain

Putting it together

Using one-hot encoding of categorical features

Continuous valued features

Regression Trees

Tree ensembles

Using multiple decision trees

Sampling with replacement

Random forest algorithm

XGBoost

When to use decision trees