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