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docs: minor typos fixed #31945

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096c0c8
minor typos fixed
Aug 14, 2025
1dde00c
typo fix
maitreytalware Aug 17, 2025
5a922e9
Merge remote-tracking branch 'upstream/main' into typo_fix
maitreytalware Aug 17, 2025
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4 changes: 2 additions & 2 deletions README.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/scikit-learn.svg
:target: https://pypi.org/project/scikit-learn/

.. |PyPi| image:: https://img.shields.io/pypi/v/scikit-learn
.. |PyPI| image:: https://img.shields.io/pypi/v/scikit-learn
:target: https://pypi.org/project/scikit-learn

.. |DOI| image:: https://zenodo.org/badge/21369/scikit-learn/scikit-learn.svg
Expand Down Expand Up @@ -77,7 +77,7 @@ classes end with ``Display``) require Matplotlib (>= |MatplotlibMinVersion|).
For running the examples Matplotlib >= |MatplotlibMinVersion| is required.
A few examples require scikit-image >= |Scikit-ImageMinVersion|, a few examples
require pandas >= |PandasMinVersion|, some examples require seaborn >=
|SeabornMinVersion| and plotly >= |PlotlyMinVersion|.
|SeabornMinVersion| and Plotly >= |PlotlyMinVersion|.

User installation
~~~~~~~~~~~~~~~~~
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2 changes: 1 addition & 1 deletion sklearn/model_selection/tests/test_validation.py
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Expand Up @@ -1208,7 +1208,7 @@ def test_learning_curve():
assert_array_almost_equal(test_scores.mean(axis=1), np.linspace(0.1, 1.0, 10))

# Cannot use assert_array_almost_equal for fit and score times because
# the values are hardware-dependant
# the values are hardware-dependent
assert fit_times.dtype == "float64"
assert score_times.dtype == "float64"

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2 changes: 1 addition & 1 deletion sklearn/utils/tests/test_validation.py
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Expand Up @@ -289,7 +289,7 @@ def test_check_array_links_to_imputer_doc_only_for_X(input_name, retype):
assert extended_msg not in ctx.value.args[0]

if input_name == "X":
# Veriy that _validate_data is automatically called with the right argument
# Verify that _validate_data is automatically called with the right argument
# to generate the same exception:
with pytest.raises(ValueError, match=f"Input {input_name} contains NaN") as ctx:
SVR().fit(data, np.ones(data.shape[0]))
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