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fast eli5.sklearn.permutation_importance? #336
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@joelrich started an issue (#317) like that but it seemingly received no feedback. I would also vote for a parallel implementation. |
The new implementation of permutation importance in scikit-learn (not yet
released) offers some parallelism:
https://scikit-learn.org/dev/modules/generated/sklearn.inspection.permutation_importance.html
<https://scikit-learn.org/dev/modules/generated/sklearn.inspection.permutation_importance.html#sklearn.inspection.permutation_importance>
|
I think @jnothman reference is the best that we currently have. Does anyone know if this will be ported to Eli? thanks, |
It seems even for relatively small training sets, model (e.g. DecisionTreeClassifier, RandomForestClassifier) training is fast, but using permutation_importance on the trained models is incredibly slow. (Currently using model.feature_importances_ as alternative) |
Is there a way to make:
perm = PermutationImportance(estimator, cv='prefit', n_iter=1).fit(X_window_test, Y_test)
fast?
currently I am running an experiment with 3,179 features and the algorithm is too slow (even with cv=prefit) is there a way to make it faster?
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