8000 ENH Added n_components_ to SparsePCA and MiniBatchSparsePCA (#16981) · scikit-learn/scikit-learn@41b18fe · GitHub
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ReksbrilMateusz Górskithomasjpfan
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ENH Added n_components_ to SparsePCA and MiniBatchSparsePCA (#16981)
* Add n_components_ attribute to SparcePCA and MiniBatchSparsePCA * Add n_components_ attribute to SparcePCA and MiniBatchSparsePCA * Add whatsnew entry * Fix documentation * Apply suggestions from code review Co-Authored-By: Thomas J Fan <thomasjpfan@gmail.com> * Add suggested changes * Update test_sparse_pca.py Co-authored-by: Mateusz Górski <mateuszg122@gmail.com> Co-authored-by: Thomas J Fan <thomasjpfan@gmail.com>
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‎doc/whats_new/v0.23.rst

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@@ -215,6 +215,9 @@ Changelog
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raise `invalid value encountered in multiply` during `fit`.
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:pr:`16718` by :user:`Gui Miotto <gui-miotto>`.
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- |Feature| Added `n_components_` attribute to :class:'decomposition.SparsePCA'
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and :class:'MiniBatchSparsePCA'. :pr:'16981' by :user:'Mateusz Górski <Reksbril>'
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:mod:`sklearn.ensemble`
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.......................
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‎sklearn/decomposition/_sparse_pca.py

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@@ -103,6 +103,11 @@ class SparsePCA(TransformerMixin, BaseEstimator):
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error_ : array
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Vector of errors at each iteration.
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n_components_ : int
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Estimated number of components.
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.. versionadded:: 0.23
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n_iter_ : int
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Number of iterations run.
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@@ -197,6 +202,7 @@ def fit(self, X, y=None):
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self.components_, axis=1)[:, np.newaxis]
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components_norm[components_norm == 0] = 1
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self.components_ /= components_norm
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self.n_components_ = len(self.components_)
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self.error_ = E
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return self
@@ -312,6 +318,11 @@ class MiniBatchSparsePCA(SparsePCA):
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components_ : array, [n_components, n_features]
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Sparse components extracted from the data.
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n_components_ : int
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Estimated number of components.
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.. versionadded:: 0.23
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n_iter_ : int
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Number of iterations run.
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@@ -403,5 +414,6 @@ def fit(self, X, y=None):
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self.components_, axis=1)[:, np.newaxis]
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components_norm[components_norm == 0] = 1
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self.components_ /= components_norm
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self.n_components_ = len(self.components_)
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return self

‎sklearn/decomposition/tests/test_sparse_pca.py

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@@ -207,3 +207,18 @@ def test_spca_error_unormalized_components(spca):
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err_msg = "normalize_components=False is not supported starting "
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with pytest.raises(NotImplementedError, match=err_msg):
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spca(normalize_components=False).fit(Y)
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@pytest.mark.parametrize("SPCA", [SparsePCA, MiniBatchSparsePCA])
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@pytest.mark.parametrize("n_components", [None, 3])
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def test_spca_n_components_(SPCA, n_components):
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rng = np.random.RandomState(0)
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n_samples, n_features = 12, 10
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X = rng.randn(n_samples, n_features)
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model = SPCA(n_components=n_components).fit(X)
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if n_components is not None:
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assert model.n_components_ == n_components
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else:
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assert model.n_components_ == n_features

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