decision trees

Pros

1. Intuitive decision rules make it easy to interpret.
2. Trees handle nonlinear features well.
3. The variable interaction is taken into account.

Cons

1. Trees are highly biased towards the training set and overfit is common.
2. There is no meaningful probability score as the output.