The default is to use your cv set! With the same training set, train a logistic regression model and a decision trees model, then evaluate them with the same cv set, and see which one does better.

Logistic regression gives you one straight boundary line; decision trees give you more complex boundary lines. With higher complexity in boundary lines, the model is able to fit itself to a more complex dataset!