scikit-learn
diff --git a/‎sklearn/linear_model/_stochastic_gradient.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/_stochastic_gradient.py
-5Lines changed: 0 additions & 5 deletions b/‎sklearn/linear_model/_stochastic_gradient.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/_stochastic_gradient.py
-5Lines changed: 0 additions & 5 deletions
@@ -80,18 +80,13 @@ class BaseSGD(SparseCoefMixin, BaseEstimator, metaclass=ABCMeta):
     """Base class for SGD classification and regression."""
 
     _parameter_constraints: dict = {
-        "penalty": [StrOptions({"l2", "l1", "elasticnet"}), None],
-        "alpha": [Interval(Real, 0, None, closed="left")],
         "C": [Interval(Real, 0, None, closed="right")],
-        "l1_ratio": [Interval(Real, 0, 1, closed="both")],
         "fit_intercept": ["boolean"],
         "max_iter": [Interval(Integral, 1, None, closed="left")],
         "tol": [Interval(Real, 0, None, closed="left"), None],
         "shuffle": ["boolean"],
         "random_state": ["random_state"],
         "verbose": ["verbose"],
-        "eta0": [Interval(Real, 0, None, closed="left")],
-        "power_t": [Interval(Real, None, None, closed="neither")],
         "early_stopping": ["boolean"],
         "validation_fraction": [Interval(Real, 0, 1, closed="neither")],
         "n_iter_no_change": [Interval(Integral, 1, None, closed="left")],