DOC Add warm start section for tree ensembles #29001
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adrinjalali
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May 13, 2024
doc/modules/ensemble.rst
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| >>> X, y = make_classification(n_samples=100, random_state=1) | ||
| >>> clf = RandomForestClassifier(n_estimators=10) | ||
| >>> clf = clf.fit(X, y) # fit with 10 trees | ||
| >>> _ = clf.set_params(n_estimators=20, warm_start=True) # set warm_start and increase num of estimators |
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Line too long, might be a good idea to move the comment to the line above?
Also, do you think it makes sense to show something about the estimator before and after the second fit? To show how it changed?
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Good idea. I just printed len(clf.estimators_).
I guess ideally we would show that the first 10 estimators are the same but I couldn't think of a good way to do that.
adrinjalali
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May 14, 2024
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We could export the trees with graphviz and show, but this is already a good improvement. Further improvements are very much welcome. Thanks @lucyleeow
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Reference Issues/PRs
closes #22041
What does this implement/fix? Explain your changes.
warm_start#24579), which is confusing. I thought about making a single section and talk about both ensemble and gradient boosted trees but thought it didn't fit withensemble.rstpage as its currently divided into sections for each estimator type.warm_starttogether withrandom_stateis poorly documented #22041). I thought about adding this section in the docstrings (withwarm_startparam or at the end) of the 6 estimators but thought this was better as we can give an example as well. Happy to change though.Any other comments?