ENH Checks n_features_in_ in preprocessing module #18577
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ogrisel
reviewed
Oct 9, 2020
| raise ValueError('X does not have the same number of features as' | ||
| ' the previously fitted data. Got {} instead of' | ||
| ' {}.'.format(X.shape[1], | ||
| self.quantiles_.shape[1])) |
ogrisel
reviewed
Oct 9, 2020
This was referenced Oct 9, 2020
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Now that #18011 is merged, I believe this is ready for merge. |
Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com> Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
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Weird, there is still conflicts in the |
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Ok, hopefully that fixed it. |
…features_in_preprocessing
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@NicolasHug I think this is ready for quick merge. |
NicolasHug
approved these changes
Oct 14, 2020
| @@ -1310,12 +1310,10 @@ def test_quantile_transform_check_error(): | |||
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| X_bad_feat = np.transpose([[0, 25, 50, 0, 0, 0, 75, 0, 0, 100], | |||
| [0, 0, 2.6, 4.1, 0, 0, 2.3, 0, 9.5, 0.1]]) | |||
| err_msg = ("X does not have the same number of features as the previously" | |||
| " fitted " "data. Got 2 instead of 3.") | |||
| err_msg = ("X has 2 features, but QuantileTransformer is expecting " | |||
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Should we remove this check since we have a common check?
| @@ -104,7 +104,8 @@ def test_fit_transform_n_bins_array(strategy, expected): | |||
| def test_invalid_n_features(): | |||
| est = KBinsDiscretizer(n_bins=3).fit(X) | |||
| bad_X = np.arange(25).reshape(5, -1) | |||
| err_msg = "Incorrect number of features. Expecting 4, received 5" | |||
| err_msg = ("X has 5 features, but KBinsDiscretizer is expecting 4 " | |||
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same here, should this just be removed?
glemaitre
approved these changes
Oct 21, 2020
thomasjpfan
added a commit
to thomasjpfan/scikit-learn
that referenced
this pull request
Oct 28, 2020
Co-authored-by: Olivier Grisel <olivier.grisel@gmail.com> Co-authored-by: Joel Nothman <joel.nothman@gmail.com> Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com> Co-authored-by: Nicolas Hug <contact@nicolas-hug.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
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Reference Issues/PRs
Continues #18514 for the preprocessing module.