Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Should HonestForest* have bootstrap=False or bootstrap=True as default #146

Closed
adam2392 opened this issue Oct 16, 2023 · 2 comments · Fixed by #274
Closed

Should HonestForest* have bootstrap=False or bootstrap=True as default #146

adam2392 opened this issue Oct 16, 2023 · 2 comments · Fixed by #274
Labels
question Further information is requested

Comments

@adam2392
Copy link
Collaborator

It is unclear what the default should be because in scikit-learn, bootstrap=True on Forests are the default.

cc: @rflperry @sampan501 mentioned that your original implementation had boostrap=False as the default. To my knowledge, there is no reason to default in HonestForests, so I'm wondering if we should stick w/ scikit-learn defaults?

@adam2392 adam2392 added the question Further information is requested label Oct 16, 2023
@rflperry
Copy link
Member

I believe this the initial HonestForest implementation took the defaults of the Generalized Random Forest package in R (GRF). Honest forests use a subsample to to learn trees due to the whole idea of "honesty". When bootstrap=True , I believe what we do (and GRF does) is bootstrap the structure learning subset of the data. In a regular forest, bootstrapping is useful as it helps to decorrelate the trees. It's not clear that this is needed on top of the normal sample splitting present in honest trees.

@adam2392
Copy link
Collaborator Author

adam2392 commented May 6, 2024

Currently, we will set bootstrap=False due to just backwards incompatibility of the unit-tests when changing, but we can explore what will happen if we change it

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
question Further information is requested
Projects
None yet
2 participants