An example that shows a predictor that overfits (low bias high variance, e.g. a full DT) vs a predictor that does not (e.g. decision stumps) would be interesting.

Maybe also a an example (or reusing the same example) that demonstrates how to use AdaBoost with non-tree models that support the sample_weight API. For instance rbf kernel SVC models (if not too expensive for an example).