MNT remove deprecated loss_function_ in SGD (scikit-learn#29095)

Author: lorentzenchr

sklearn/linear_model/_passive_aggressive.py

@@ -142,13 +142,6 @@ class PassiveAggressiveClassifier(BaseSGDClassifier):
         Number of weight updates performed during training.
         Same as ``(n_iter_ * n_samples + 1)``.
 
-    loss_function_ : callable
-        Loss function used by the algorithm.
-
-         .. deprecated:: 1.4
-            Attribute `loss_function_` was deprecated in version 1.4 and will be
-            removed in 1.6.
-
     See Also
     --------
     SGDClassifier : Incrementally trained logistic regression.

sklearn/linear_model/_perceptron.py

@@ -123,10 +123,6 @@ class Perceptron(BaseSGDClassifier):
     intercept_ : ndarray of shape (1,) if n_classes == 2 else (n_classes,)
         Constants in decision function.
 
-    loss_function_ : concrete LossFunction
-        The function that determines the loss, or difference between the
-        output of the algorithm and the target values.
-
     n_features_in_ : int
         Number of features seen during :term:`fit`.
 

sklearn/linear_model/_stochastic_gradient.py

@@ -20,7 +20,7 @@
 )
 from ..exceptions import ConvergenceWarning
 from ..model_selection import ShuffleSplit, StratifiedShuffleSplit
-from ..utils import check_random_state, compute_class_weight, deprecated
+from ..utils import check_random_state, compute_class_weight
 from ..utils._param_validation import Hidden, Interval, StrOptions
 from ..utils.extmath import safe_sparse_dot
 from ..utils.metaestimators import available_if
@@ -321,16 +321,6 @@ def _make_validation_score_cb(
             classes=classes,
         )
 
-    # TODO(1.6): Remove
-    # mypy error: Decorated property not supported
-    @deprecated(  # type: ignore
-        "Attribute `loss_function_` was deprecated in version 1.4 and will be removed "
-        "in 1.6."
-    )
-    @property
-    def loss_function_(self):
-        return self._loss_function_
-
 
 def _prepare_fit_binary(est, y, i, input_dtype):
     """Initialization for fit_binary.
@@ -1159,12 +1149,6 @@ class SGDClassifier(BaseSGDClassifier):
         The actual number of iterations before reaching the stopping criterion.
         For multiclass fits, it is the maximum over every binary fit.
 
-    loss_function_ : concrete ``LossFunction``
-
-        .. deprecated:: 1.4
-            Attribute `loss_function_` was deprecated in version 1.4 and will be
-            removed in 1.6.
-
     classes_ : array of shape (n_classes,)
 
     t_ : int
@@ -2186,12 +2170,6 @@ class SGDOneClassSVM(BaseSGD, OutlierMixin):
         Number of weight updates performed during training.
         Same as ``(n_iter_ * n_samples + 1)``.
 
-    loss_function_ : concrete ``LossFunction``
-
-        .. deprecated:: 1.4
-            ``loss_function_`` was deprecated in version 1.4 and will be removed in
-            1.6.
-
     n_features_in_ : int
         Number of features seen during :term:`fit`.
 

sklearn/linear_model/tests/test_sgd.py

@@ -2216,19 +2216,6 @@ def test_sgd_numerical_consistency(SGDEstimator):
     assert_allclose(sgd_64.coef_, sgd_32.coef_)
 
 
-# TODO(1.6): remove
-@pytest.mark.parametrize("Estimator", [SGDClassifier, SGDOneClassSVM])
-def test_loss_attribute_deprecation(Estimator):
-    # Check that we raise the proper deprecation warning if accessing
-    # `loss_function_`.
-    X = np.array([[1, 2], [3, 4]])
-    y = np.array([1, 0])
-    est = Estimator().fit(X, y)
-
-    with pytest.warns(FutureWarning, match="`loss_function_` was deprecated"):
-        est.loss_function_
-
-
 # TODO(1.7): remove
 @pytest.mark.parametrize("Estimator", [SGDClassifier, SGDRegressor, SGDOneClassSVM])
 def test_passive_aggressive_deprecated_average(Estimator):