scikit-learn
diff --git a/‎doc/whats_new/v1.6.rst
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+3-3Lines changed: 3 additions & 3 deletions b/‎doc/whats_new/v1.6.rst
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diff --git a/‎sklearn/linear_model/tests/test_ridge.py
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@@ -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
 
@@ -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