8000 fix tests. Add whats new on the current changes · scikit-learn/scikit-learn@827f795 · GitHub
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ciku
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fix tests. Add whats new on the current changes
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‎doc/whats_new/v1.1.rst

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@@ -60,7 +60,7 @@ Changelog
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add this information to the plot.
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:pr:`21038` by :user:`Guillaume Lemaitre <glemaitre>`.
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- |Enhancement| :class:`cluster.SpectralClustering` and :func:`cluster.spectral`
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- |Enhancement| :class:`cluster.SpectralClustering` and :func:`cluster.spectral`
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now include the new `'cluster_qr'` method from :func:`cluster.cluster_qr`
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that clusters samples in the embedding space as an alternative to the existing
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`'kmeans'` and `'discrete'` methods.
@@ -105,12 +105,12 @@ Changelog
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- |API| Adds :meth:`get_feature_names_out` to :class:`impute.SimpleImputer`,
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:class:`impute.KNNImputer`, :class:`impute.IterativeImputer`, and
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:class:`impute.MissingIndicator`. :pr:`21078` by `Thomas Fan`_.
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- |API| The `verbose` parameter was deprecated for :class:`impute.SimpleImputer`.
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A warning will always be raised upon the removal of empty columns.
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:pr:`21448` by :user:`Oleh Kozynets <OlehKSS>` and
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:user:`Christian Ritter <chritter>.
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- |Fix| Fix a bug in :class:`linear_model.RidgeClassifierCV` where the method
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`predict` was performing an `argmax` on the scores obtained from
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`decision_function` instead of returning the multilabel indicator matrix.
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instead of `__init__`.
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:pr:`21434` by :user:`Krum Arnaudov <krumeto>`.
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:mod: `sklearn.decomposition.KernelPCA`
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..........................
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-[Fix] :class:`decomposition.KernelPCA` now validates input parameters in `fit` instead of `__init__`
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:pr:`21567` by :user: `Maggie Chege <MaggieChege>`
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:mod:`sklearn.svm`
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..................
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- |Fix| :class:`smv.NuSVC`, :class:`svm.NuSVR`, :class:`svm.SVC`,
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:class:`svm.SVR`, :class:`svm.OneClassSVM` now validate input
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:class:`svm.SVR`, :class:`svm.OneClassSVM` now validate input
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parameters in `fit` instead of `__init__`.
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:pr:`21436` by :user:`Haidar Almubarak <Haidar13 >`.
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‎sklearn/decomposition/_kernel_pca.py

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@@ -427,14 +427,13 @@ def fit(self, X, y=None):
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self : object
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Returns the instance itself.
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"""
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if self.fit_inverse_transform and self.kernel == "precomputed":
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raise ValueError("Cannot fit_inverse_transform with a precomputed kernel.")
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X = self._validate_data(X, accept_sparse="csr", copy=self.copy_X)
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self._centerer = KernelCenterer()
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K = self._get_kernel(X)
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self._fit_transform(K)
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if self.fit_inverse_transform and self.kernel == "precomputed":
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raise ValueError("Cannot fit_inverse_transform with a precomputed kernel.")
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if self.fit_inverse_transform:
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# no need to use the kernel to transform X, use shortcut expression
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X_transformed = self.eigenvectors_ * np.sqrt(self.eigenvalues_)

‎sklearn/decomposition/tests/test_kernel_pca.py

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@@ -79,7 +79,10 @@ def test_kernel_pca_invalid_parameters():
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ValueError.
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"""
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with pytest.raises(ValueError):
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KernelPCA(10, fit_inverse_transform=True, kernel="precomputed")
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estimator = KernelPCA(
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n_components=10, fit_inverse_transform=True, kernel="precomputed"
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)
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estimator.fit(np.random.randn(10, 10))
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def test_kernel_pca_consistent_transform():

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