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DOC fix typos introduced in #29842 #29886

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Merged
merged 2 commits into from
Sep 18, 2024
Merged

DOC fix typos introduced in #29842 #29886

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3dfc5b6
fix typos
glemaitre Sep 18, 2024
3607a96
fix typos
glemaitre Sep 18, 2024
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6 changes: 3 additions & 3 deletions doc/whats_new/v1.6.rst
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Expand Up @@ -257,10 +257,10 @@ Changelog
for the calculation of test scores.
:pr:`29419` by :user:`Shruti Nath <snath-xoc>`.

- |Fix| :class:`linear_model.RidgeCV` now properly use predictions the same scale as the
target seen during `fit`. Those predictions are stored in `cv_results_` when when
- |Fix| :class:`linear_model.RidgeCV` now properly uses predictions on the same scale as
the target seen during `fit`. These predictions are stored in `cv_results_` when
`scoring != None`. Previously, the predictions were rescaled by the square root of the
sample weights and offset by the mean of the target leading to an incorrect estimate
sample weights and offset by the mean of the target, leading to an incorrect estimate
of the score.
:pr:`29842` by :user:`Guillaume Lemaitre <glemaitre>`,
:user:`Jérôme Dockes <jeromedockes>` and
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8 changes: 4 additions & 4 deletions sklearn/linear_model/tests/test_ridge.py
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Expand Up @@ -2261,12 +2261,12 @@ def test_ridge_cv_results_predictions(with_sample_weight, fit_intercept, n_targe
"""Check that the predictions stored in `cv_results_` are on the original scale.

The GCV approach works on scaled data: centered by an offset and scaled by the
squared root of the sample weights. Thus, previous to compute scores, the
predictions need to be scaled back to the original scale. Those predictions are the
ones stored in `cv_results_` in `RidgeCV`.
square root of the sample weights. Thus, prior to computing scores, the
predictions need to be scaled back to the original scale. These predictions are
the ones stored in `cv_results_` in `RidgeCV`.

In this test, we check that the internal predictions stored in `cv_results_` are
equivalent to a naive LOO-CV grid-search with a `Ridge` estimator.
equivalent to a naive LOO-CV grid search with a `Ridge` estimator.

Non-regression test for:
https://github.com/scikit-learn/scikit-learn/issues/13998
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