How to use custom classifiers in ensemble classifiers in sklearn?

Question

I read that the builtin ensemble methods in sklearn use decision trees as the base classifiers. Is it possible to use custom classifiers instead?

Answer 1

If you mean the random forest classes, then no, this is currently not possible. The option to allow other estimators was discussed on the scikit-learn mailing list last January, but I don't believe any actual code has come out that discussion.

Answer 2

If you use sklearn.ensemble.AdaBoostClassifier, then the answer is yes: scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html You can assign base_estimator yourself.

Answer 3

I don't know if it helps, but you can very easily stack/combine custom classifiers using the Pipeline utilities: http://scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html#pipelining