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DOC ensures SparsePCA docstring passes numpydoc validation #20395

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Jul 13, 2021
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DOC ensures SparsePCA docstring passes numpydoc validation #20395

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1de2543
SparsePCA now complies with numpydoc style.
ijpulidos Jun 26, 2021
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Apply suggestions from code review
glemaitre Jul 13, 2021
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glemaitre Jul 13, 2021
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1 change: 0 additions & 1 deletion maint_tools/test_docstrings.py
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Expand Up @@ -190,7 +190,6 @@
"SimpleImputer",
"SkewedChi2Sampler",
"SparseCoder",
"SparsePCA",
"SparseRandomProjection",
"SpectralBiclustering",
"SpectralClustering",
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15 changes: 9 additions & 6 deletions sklearn/decomposition/_sparse_pca.py
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Expand Up @@ -40,6 +40,7 @@ class SparsePCA(TransformerMixin, BaseEstimator):
Tolerance for the stopping condition.

method : {'lars', 'cd'}, default='lars'
Method to be used for optimization.
lars: uses the least angle regression method to solve the lasso problem
(linear_model.lars_path)
cd: uses the coordinate descent method to compute the
Expand Down Expand Up @@ -93,6 +94,13 @@ class SparsePCA(TransformerMixin, BaseEstimator):

.. versionadded:: 0.24

See Also
--------
PCA : Principal Component Analysis implementation.
MiniBatchSparsePCA : Mini batch variant of `SparsePCA` that is faster but less
accurate.
DictionaryLearning : Generic dictionary learning problem using a sparse code.

Examples
--------
>>> import numpy as np
Expand All @@ -108,12 +116,6 @@ class SparsePCA(TransformerMixin, BaseEstimator):
>>> # most values in the components_ are zero (sparsity)
>>> np.mean(transformer.components_ == 0)
0.9666...

See Also
--------
PCA
MiniBatchSparsePCA
DictionaryLearning
"""

def __init__(
Expand Down Expand Up @@ -153,6 +155,7 @@ def fit(self, X, y=None):
and n_features is the number of features.

y : Ignored
Not used, present here for API consistency by convention.

Returns
-------
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