FEAT allow RFE(CV) be used with pemutation_importance
#32251
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pemutation_importance
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Thanks for the PR. This is very useful. Please indeed update the example and add a changelog entry.
EDIT: here are the instructions for the changelog entry: https://github.com/scikit-learn/scikit-learn/blob/main/doc/whats_new/upcoming_changes/README.md
| This allows methods like :func:`permutation_importance` to extract the relevant features | ||
| from its test set. |
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| This allows methods like :func:`permutation_importance` to extract the relevant features | |
| from its test set. | |
| This allows methods like :func:`permutation_importance` and similar tools to | |
| iteratively extract the previously selected features from a test set. |
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yeah I realized it was not very clear so I planned to change it to:
" This allows methods that need a test set, like :func:permutation_importance, to know which
features of to use in their predictions."
sklearn/feature_selection/_rfe.py
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| `feature_indices` which stores the index of the features in the full dataset | ||
| that have not been eliminated yet. | ||
| `feature_indices` allows RFE to be used with permutation importance, as |
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| `feature_indices` allows RFE to be used with permutation importance, as | |
| `feature_indices` allows `RFE` to be used with permutation importance, as |
sklearn/feature_selection/_rfe.py
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| `feature_indices` which stores the index of the features in the full dataset | ||
| that have not been eliminated yet. | ||
| `feature_indices` allows RFECV to be used with permutation importance, as |
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| `feature_indices` allows RFECV to be used with permutation importance, as | |
| `feature_indices` allows `RFECV` to be used with permutation importance, as |
| If `callable`, overrides the default feature importance getter. | ||
| The callable is passed with the fitted estimator and it should | ||
| return importance for each feature. | ||
| return importance for each feature. When it accepts it, the callable is passed |
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While we are at it, can you please fix the missing backtick before :class: to get the ~sklearn.pipeline.Pipeline link to render properly in HTML?
Reference Issues/PRs
Fixes #32201
What does this implement/fix? Explain your changes.
To be used in RFE and RFECV,
permutation_importanceneeds to be aware of which features were already eliminated by the procedure to reduce its test dataset.This PR adds a
feature_indicesparameter tosklearn.feature_selection._base._get_feature_importancesthat is given to theimportance_getterso that it is aware of which features to compute the importance of.Any other comments?
The new feature is added to the test suite and illustrated in the
RFECVdoc example.@glemaitre @ogrisel