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Update _coordinate_descent.py #30416

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Update _coordinate_descent.py #30416

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9a537a5
Update _coordinate_descent.py
prempraneethkota Dec 6, 2024
3fef731
Update _coordinate_descent.py
prempraneethkota Dec 6, 2024
0f8f5c4
Update _coordinate_descent.py
prempraneethkota Dec 6, 2024
5f9299f
Update _coordinate_descent.py
prempraneethkota Dec 6, 2024
e96ee60
Fix handling of refit parameter in LassoCV
prempraneethkota Dec 6, 2024
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10 changes: 9 additions & 1 deletion 10 sklearn/linear_model/_coordinate_descent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -910,7 +910,7 @@ def __init__(
warm_start=False,
positive=False,
random_state=None,
selection="cyclic",
selection="cyclic"
):
self.alpha = alpha
self.l1_ratio = l1_ratio
Expand Down Expand Up @@ -2052,7 +2052,9 @@ def __init__(
positive=False,
random_state=None,
selection="cyclic",
refit=True,
):
self.refit = refit
super().__init__(
eps=eps,
n_alphas=n_alphas,
Expand Down Expand Up @@ -2082,6 +2084,7 @@ def __sklearn_tags__(self):
return tags

def fit(self, X, y, sample_weight=None, **params):
params.pop('refit', None)
"""Fit Lasso model with coordinate descent.

Fit is on grid of alphas and best alpha estimated by cross-validation.
Expand Down Expand Up @@ -2119,8 +2122,13 @@ def fit(self, X, y, sample_weight=None, **params):
self : object
Returns an instance of fitted model.
"""

return super().fit(X, y, sample_weight=sample_weight, **params)

if self.refit:
self._fit(X, y)

return self

class ElasticNetCV(RegressorMixin, LinearModelCV):
"""Elastic Net model with iterative fitting along a regularization path.
Expand Down
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