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[MRG+1] add groups support to RFECV #9656
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Needs a test. |
jnothman
reviewed
Sep 1, 2017
| X = iris.data | ||
| y = (iris.target > 0).astype(int) | ||
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| # test basic cv |
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Why is this needed? Isn't it tested elsewhere?
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otherwise LGTM |
jnothman
reviewed
Sep 2, 2017
| @@ -1250,3 +1254,30 @@ def test_cross_val_predict_sparse_prediction(): | |||
| preds_sparse = cval.cross_val_predict(classif, X_sparse, y_sparse, cv=10) | |||
| preds_sparse = preds_sparse.toarray() | |||
| assert_array_almost_equal(preds_sparse, preds) | |||
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| def test_rfe_cv(): | |||
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Silly me, this shouldn't be in test_cross_validation. It should be in feature_selection/tests/test_rfe.py
glemaitre
reviewed
Sep 5, 2017
| cv=GroupKFold(n_splits=2) | ||
| ) | ||
| est_groups.fit(X, y, groups=groups) | ||
| assert(est_groups.n_features_ > 0) |
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You don't need the paranthesis
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| def test_rfe_cv_groups(): | ||
| # test cv with groups |
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you can remove the comment since this is already implied by the name of the function
| y = (iris.target > 0).astype(int) | ||
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| est_groups = RFECV( | ||
| estimator=RandomForestClassifier(), |
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could you set the random_state of the estimator that take one.
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Good job @adamgreenhall, thanks ! |
jwjohnson314
pushed a commit
to jwjohnson314/scikit-learn
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this pull request
Dec 18, 2017
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Reference Issue
related to #8127
What does this implement/fix? Explain your changes.
Adding support for cv groups (eg
LeaveOneGroupOut) toRFECV.