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FIX: Change limits of power_t param to [0, inf) #31474

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Merged
merged 8 commits into from
Jun 10, 2025
Merged

FIX: Change limits of power_t param to [0, inf) #31474

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2643768
fix: change limits of power_t param to [0, inf)
ritvi-alagusankar Jun 3, 2025
17d4a68
style: formatting
ritvi-alagusankar Jun 3, 2025
523b38f
fix: minor changes to docstring
ritvi-alagusankar Jun 3, 2025
ad996aa
fix: handle the parameter limits using a deprecation cycle
ritvi-alagusankar Jun 3, 2025
958bc39
style: fix formatting
ritvi-alagusankar Jun 3, 2025
29f9b21
test: minor changes to test
ritvi-alagusankar Jun 3, 2025
614f150
fix: add changelog entry
ritvi-alagusankar Jun 4, 2025
28086a6
fix: minor change to changelog
ritvi-alagusankar Jun 4, 2025
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6 changes: 6 additions & 0 deletions doc/whats_new/upcoming_changes/sklearn.linear_model/31474.api.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
- :class:`linear_model.SGDClassifier`, :class:`linear_model.SGDRegressor`, and
:class:`linear_model.SGDOneClassSVM` now deprecate negative values for the
`power_t` parameter. Using a negative value will raise a warning in version 1.8
and will raise an error in version 1.10. A value in the range [0.0, inf) must be used
instead.
By :user:`Ritvi Alagusankar <ritvi-alagusankar>`
43 changes: 40 additions & 3 deletions sklearn/linear_model/_stochastic_gradient.py
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Original file line number Diff line number Diff line change
Expand Up @@ -731,6 +731,15 @@ def _fit(
),
ConvergenceWarning,
)

if self.power_t < 0:
warnings.warn(
"Negative values for `power_t` are deprecated in version 1.8 "
"and will raise an error in 1.10. "
"Use values in the range [0.0, inf) instead.",
FutureWarning,
)

return self

def _fit_binary(self, X, y, alpha, C, sample_weight, learning_rate, max_iter):
Expand Down Expand Up @@ -1082,7 +1091,11 @@ class SGDClassifier(BaseSGDClassifier):

power_t : float, default=0.5
The exponent for inverse scaling learning rate.
Values must be in the range `(-inf, inf)`.
Values must be in the range `[0.0, inf)`.

.. deprecated:: 1.8
Negative values for `power_t` are deprecated in version 1.8 and will raise
an error in 1.10. Use values in the range [0.0, inf) instead.

early_stopping : bool, default=False
Whether to use early stopping to terminate training when validation
Expand Down Expand Up @@ -1585,6 +1598,14 @@ def _fit(
ConvergenceWarning,
)

if self.power_t < 0:
warnings.warn(
"Negative values for `power_t` are deprecated in version 1.8 "
"and will raise an error in 1.10. "
"Use values in the range [0.0, inf) instead.",
FutureWarning,
)

return self

@_fit_context(prefer_skip_nested_validation=True)
Expand Down Expand Up @@ -1880,7 +1901,11 @@ class SGDRegressor(BaseSGDRegressor):

power_t : float, default=0.25
The exponent for inverse scaling learning rate.
Values must be in the range `(-inf, inf)`.
Values must be in the range `[0.0, inf)`.

.. deprecated:: 1.8
Negative values for `power_t` are deprecated in version 1.8 and will raise
an error in 1.10. Use values in the range [0.0, inf) instead.

early_stopping : bool, default=False
Whether to use early stopping to terminate training when validation
Expand Down Expand Up @@ -2118,7 +2143,11 @@ class SGDOneClassSVM(OutlierMixin, BaseSGD):

power_t : float, default=0.5
The exponent for inverse scaling learning rate.
Values must be in the range `(-inf, inf)`.
Values must be in the range `[0.0, inf)`.

.. deprecated:: 1.8
Negative values for `power_t` are deprecated in version 1.8 and will raise
an error in 1.10. Use values in the range [0.0, inf) instead.

warm_start : bool, default=False
When set to True, reuse the solution of the previous call to fit as
Expand Down Expand Up @@ -2490,6 +2519,14 @@ def _fit(
ConvergenceWarning,
)

if self.power_t < 0:
warnings.warn(
"Negative values for `power_t` are deprecated in version 1.8 "
"and will raise an error in 1.10. "
"Use values in the range [0.0, inf) instead.",
FutureWarning,
)

return self

@_fit_context(prefer_skip_nested_validation=True)
Expand Down
30 changes: 30 additions & 0 deletions sklearn/linear_model/tests/test_sgd.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
import pickle
import warnings
from unittest.mock import Mock

import joblib
Expand Down Expand Up @@ -507,6 +508,35 @@ def test_sgd_failing_penalty_validation(Estimator):
clf.fit(X, Y)


# TODO(1.10): remove this test
@pytest.mark.parametrize(
"klass",
[
SGDClassifier,
SparseSGDClassifier,
SGDRegressor,
SparseSGDRegressor,
SGDOneClassSVM,
SparseSGDOneClassSVM,
],
)
def test_power_t_limits(klass):
"""Check that a warning is raised when `power_t` is negative."""

# Check that negative values of `power_t` raise a warning
clf = klass(power_t=-1.0)
with pytest.warns(
FutureWarning, match="Negative values for `power_t` are deprecated"
):
clf.fit(X, Y)

# Check that values of 'power_t in range [0, inf) do not raise a warning
with warnings.catch_warnings(record=True) as w:
clf = klass(power_t=0.5)
clf.fit(X, Y)
assert len(w) == 0


###############################################################################
# Classification Test Case

Expand Down