MAINT Clean deprecation for 1.2: KernelPCA (#24406)

jeremiedbb · web-flow · commit 85c2c3a4990a · 2022-09-12T11:01:03.000+02:00
diff --git a/sklearn/decomposition/_kernel_pca.py b/sklearn/decomposition/_kernel_pca.py
@@ -16,7 +16,6 @@
     _check_psd_eigenvalues,
 )
 from ..utils._param_validation import Interval, StrOptions
-from ..utils.deprecation import deprecated
 from ..exceptions import NotFittedError
 from ..base import BaseEstimator, TransformerMixin, _ClassNamePrefixFeaturesOutMixin
 from ..preprocessing import KernelCenterer
@@ -155,24 +154,10 @@ class KernelPCA(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimato
         If `n_components` and `remove_zero_eig` are not set,
         then all values are stored.
 
-    lambdas_ : ndarray of shape (n_components,)
-        Same as `eigenvalues_` but this attribute is deprecated.
-
-        .. deprecated:: 1.0
-           `lambdas_` was renamed to `eigenvalues_` in version 1.0 and will be
-           removed in 1.2.
-
     eigenvectors_ : ndarray of shape (n_samples, n_components)
         Eigenvectors of the centered kernel matrix. If `n_components` and
         `remove_zero_eig` are not set, then all components are stored.
 
-    alphas_ : ndarray of shape (n_samples, n_components)
-        Same as `eigenvectors_` but this attribute is deprecated.
-
-        .. deprecated:: 1.0
-           `alphas_` was renamed to `eigenvectors_` in version 1.0 and will be
-           removed in 1.2.
-
     dual_coef_ : ndarray of shape (n_samples, n_features)
         Inverse transform matrix. Only available when
         ``fit_inverse_transform`` is True.
@@ -310,25 +295,6 @@ def __init__(
         self.n_jobs = n_jobs
         self.copy_X = copy_X
 
-    # TODO: Remove in 1.2
-    # mypy error: Decorated property not supported
-    @deprecated(  # type: ignore
-        "Attribute `lambdas_` was deprecated in version 1.0 and will be "
-        "removed in 1.2. Use `eigenvalues_` instead."
-    )
-    @property
-    def lambdas_(self):
-        return self.eigenvalues_
-
-    # mypy error: Decorated property not supported
-    @deprecated(  # type: ignore
-        "Attribute `alphas_` was deprecated in version 1.0 and will be "
-        "removed in 1.2. Use `eigenvectors_` instead."
-    )
-    @property
-    def alphas_(self):
-        return self.eigenvectors_
-
     def _get_kernel(self, X, Y=None):
         if callable(self.kernel):
             params = self.kernel_params or {}
diff --git a/sklearn/decomposition/tests/test_kernel_pca.py b/sklearn/decomposition/tests/test_kernel_pca.py
@@ -516,24 +516,6 @@ def test_32_64_decomposition_shape():
     assert kpca.fit_transform(X).shape == kpca.fit_transform(X.astype(np.float32)).shape
 
 
-# TODO: Remove in 1.2
-def test_kernel_pca_lambdas_deprecated():
-    kp = KernelPCA()
-    kp.eigenvalues_ = None
-    msg = r"Attribute `lambdas_` was deprecated in version 1\.0"
-    with pytest.warns(FutureWarning, match=msg):
-        kp.lambdas_
-
-
-# TODO: Remove in 1.2
-def test_kernel_pca_alphas_deprecated():
-    kp = KernelPCA(kernel="precomputed")
-    kp.eigenvectors_ = None
-    msg = r"Attribute `alphas_` was deprecated in version 1\.0"
-    with pytest.warns(FutureWarning, match=msg):
-        kp.alphas_
-
-
 def test_kernel_pca_feature_names_out():
     """Check feature names out for KernelPCA."""
     X, *_ = make_blobs(n_samples=100, n_features=4, random_state=0)
