This is a visualization of a decision tree and the associated decision boundary for the binary classifier. The tree visualizer uses graphviz and the decision boundary uses a function based on matplotlib's pyplot. The well-known make_moons dataset is used, and a decision tree model is trained on it (including hyperparamter tuning). The decision tree boundary is compared to that of a tree with default choices of parameters (which results in overfitting on this dataset).