8000 [MRG] LogReg: Check if l1_ratio is None when using elasticnet by joseortiz3 · Pull Request #25925 · scikit-learn/scikit-learn · GitHub
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[MRG] LogReg: Check if l1_ratio is None when using elasticnet #25925

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Merged
merged 6 commits into from
Mar 22, 2023
Merged

[MRG] LogReg: Check if l1_ratio is None when using elasticnet #25925

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185f96e
[MRG] LogisticRegression: Check if l1_ratio is None when using Elasti…
joseortiz3 Mar 21, 2023
fdb3aff
Added test to check that error message is helpful
joseortiz3 Mar 21, 2023
fce348e
Added a blank line to match the code formatting
joseortiz3 Mar 21, 2023
c94fe01
Try to fix linter fail that says file would be reformatted
joseortiz3 Mar 21, 2023
2e94e3a
Update sklearn/linear_model/tests/test_logistic.py
jeremiedbb Mar 22, 2023
ac6aa63
cln
jeremiedbb Mar 22, 2023
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3 changes: 3 additions & 0 deletions sklearn/linear_model/_logistic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1168,6 +1168,9 @@ def fit(self, X, y, sample_weight=None):
"(penalty={})".format(self.penalty)
)

if self.penalty == "elasticnet" and self.l1_ratio is None:
raise ValueError("l1_ratio must be specified when penalty is elasticnet.")

# TODO(1.4): Remove "none" option
if self.penalty == "none":
warnings.warn(
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9 changes: 9 additions & 0 deletions sklearn/linear_model/tests/test_logistic.py
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739A
Original file line number Diff line number Diff line change
Expand Up @@ -227,6 +227,15 @@ def test_check_solver_option(LR):
lr.fit(X, y)


@pytest.mark.parametrize("LR", [LogisticRegression, LogisticRegressionCV])
def test_elasticnet_l1_ratio_err_helpful(LR):
# Check that an informative error message is raised when penalty="elasticnet"
# but l1_ratio is not specified.
model = LR(penalty="elasticnet", solver="saga")
with pytest.raises(ValueError, match=r".*l1_ratio.*"):
model.fit(np.array([[1, 2], [3, 4]]), np.array([0, 1]))


@pytest.mark.parametrize("solver", ["lbfgs", "newton-cg", "sag", "saga"])
def test_multinomial_binary(solver):
# Test multinomial LR on a binary problem.
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0