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DOC Add link to plot_lasso_and_elasticnet.py example in linear model #30587

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DOC Add link to plot_lasso_and_elasticnet.py example in linear model …
Jan 5, 2025
0f6758b
DOC Add link to plot_lasso_and_elasticnet.py example in linear model …
Jan 5, 2025
c93e1bd
DOC Add link to plot_lasso_and_elasticnet.py example in linear model …
Jan 5, 2025
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DOC Add link to plot_lasso_and_elasticnet.py example in linear model …
Jan 6, 2025
b17909f
Merge branch 'scikit-learn:main' into update-docs
marouaneaka Jan 6, 2025
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DOC Add link to plot_lasso_and_elasticnet.py example in linear model …
Jan 6, 2025
df75a5f
added doc to ard regression
Jan 8, 2025
7fc42c8
Merge branch 'main' into update-docs
marouaneaka Jan 8, 2025
b6064d0
ARD reg documentation, usage example moved next to comparaison example
Jan 10, 2025
c91e737
lint fixed line char limit
Jan 10, 2025
39542e0
fixed ref to ard reg example
Jan 11, 2025
645bd17
fixed ref to ard reg example lint fix
Jan 11, 2025
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15 changes: 10 additions & 5 deletions sklearn/linear_model/_bayes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -538,11 +538,6 @@ class ARDRegression(RegressorMixin, LinearModel):
--------
BayesianRidge : Bayesian ridge regression.

Notes
-----
For an example, see :ref:`examples/linear_model/plot_ard.py
<sphx_glr_auto_examples_linear_model_plot_ard.py>`.

References
----------
D. J. C. MacKay, Bayesian nonlinear modeling for the prediction
Expand All @@ -564,6 +559,16 @@ class ARDRegression(RegressorMixin, LinearModel):
ARDRegression()
>>> clf.predict([[1, 1]])
array([1.])

For examples, refer to:

- :ref:`sphx_glr_auto_examples_linear_model_plot_ard.py`:
Demonstrates ARD Regression.

- :ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`:
Showcases ARD Regression alongside Lasso and Elastic-Net for sparse signal
recovery, addressing noise and feature correlation.

"""

_parameter_constraints: dict = {
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8 changes: 8 additions & 0 deletions sklearn/linear_model/_coordinate_descent.py
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Expand Up @@ -875,6 +875,10 @@ class ElasticNet(MultiOutputMixin, RegressorMixin, LinearModel):
1.451...
>>> print(regr.predict([[0, 0]]))
[1.451...]

For an example showcasing Elastic-Net alongside Lasso and ARD Regression for sparse
signal recovery in the presence of noise and feature correlation, see:
:ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`.
"""

# "check_input" is used for optimisation and isn't something to be passed
Expand Down Expand Up @@ -1306,6 +1310,10 @@ class Lasso(ElasticNet):
[0.85 0. ]
>>> print(clf.intercept_)
0.15...

For an example comparing Lasso with other L1-based regression models
(Elastic-Net and ARD Regression) on sparse and noisy data, see:
:ref:`sphx_glr_auto_examples_linear_model_plot_lasso_and_elasticnet.py`.
"""

_parameter_constraints: dict = {
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