Combining random forest models in scikit learn

Question

I have two RandomForestClassifier models, and I would like to combine them into one meta model. They were both trained using similar, but different, data. How can I do this?

Answer 1

In addition to @mgoldwasser solution, an alternative is to make use of warm_start when training your forest. In Scikit-Learn 0.16-dev, you can now do the following:

# First build 100 trees on X1, y1
clf = RandomForestClassifier(n_estimators=100, warm_start=True)
clf.fit(X1, y1)

# Build 100 additional trees on X2, y2
clf.set_params(n_estimators=200)
clf.fit(X2, y2)