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DOC add links to plot_ridge_coeffs example #31454

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DOC add links to plot_ridge_coeffs example #31454

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73892e3
DOC add links to plot_ridge_coeffs example
lsakovykh May 29, 2025
bba65c3
Rephrase link to ridge example in linear_model.rst
lsakovykh May 31, 2025
11051ed
Apply formatting and phrasing suggestions from review
lsakovykh May 31, 2025
a2c9b8d
Style: fix trailing whitespace and blank line
lsakovykh Jun 1, 2025
c23c63b
Style: fix link formatting and remove trailing whitespace
lsakovykh Jun 1, 2025
9dc1eb4
DOC: Add example links to Ridge estimators docstrings (addressing rev…
lsakovykh Jun 2, 2025
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2 changes: 2 additions & 0 deletions doc/modules/linear_model.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -108,6 +108,8 @@ of squares:
The complexity parameter :math:`\alpha \geq 0` controls the amount
of shrinkage: the larger the value of :math:`\alpha`, the greater the amount
of shrinkage and thus the coefficients become more robust to collinearity.
See :ref:`Ridge coefficients as a function of the L2 Regularization <sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py>`
for more details.

.. figure:: ../auto_examples/linear_model/images/sphx_glr_plot_ridge_path_001.png
:target: ../auto_examples/linear_model/plot_ridge_path.html
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20 changes: 20 additions & 0 deletions sklearn/linear_model/_ridge.py
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Expand Up @@ -436,6 +436,10 @@ def ridge_regression(
reasons, using `alpha = 0` with the `Ridge` object is not advised.
Instead, you should use the :class:`LinearRegression` object.

For an example on how the model coefficients
vary with the regularization strength, see
:ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`.

If an array is passed, penalties are assumed to be specific to the
targets. Hence they must correspond in number.

Expand Down Expand Up @@ -1038,6 +1042,10 @@ class Ridge(MultiOutputMixin, RegressorMixin, _BaseRidge):
If an array is passed, penalties are assumed to be specific to the
targets. Hence they must correspond in number.

See :ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`
for an example on how the model coefficients
vary with the regularization strength.

fit_intercept : bool, default=True
Whether to fit the intercept for this model. If set
to false, no intercept will be used in calculations
Expand Down Expand Up @@ -1365,6 +1373,10 @@ class RidgeClassifier(_RidgeClassifierMixin, _BaseRidge):
:class:`~sklearn.linear_model.LogisticRegression` or
:class:`~sklearn.svm.LinearSVC`.

For an example on how the model coefficients vary
with the regularization strength, see
:ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`.

fit_intercept : bool, default=True
Whether to calculate the intercept for this model. If set to false, no
intercept will be used in calculations (e.g. data is expected to be
Expand Down Expand Up @@ -2533,6 +2545,10 @@ class RidgeCV(MultiOutputMixin, RegressorMixin, _BaseRidgeCV):
:class:`~sklearn.svm.LinearSVC`.
If using Leave-One-Out cross-validation, alphas must be strictly positive.

For an example on how the model coefficients vary
with the regularization strength, see
:ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`.

fit_intercept : bool, default=True
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
Expand Down Expand Up @@ -2717,6 +2733,10 @@ class RidgeClassifierCV(_RidgeClassifierMixin, _BaseRidgeCV):
:class:`~sklearn.svm.LinearSVC`.
If using Leave-One-Out cross-validation, alphas must be strictly positive.

For an example on how the model coefficients vary
with the regularization strength, see
:ref:`sphx_glr_auto_examples_linear_model_plot_ridge_coeffs.py`.

fit_intercept : bool, default=True
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
Expand Down