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DOC Ensure _dict_learning.dict_learning passes numpydoc validation #24316

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merged 2 commits into from
Sep 3, 2022
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DOC Ensure _dict_learning.dict_learning passes numpydoc validation #24316

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aac28b7
correct docstring fro dict_learningn
maikia Sep 2, 2022
70aba78
shorten the lines
maikia Sep 2, 2022
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16 changes: 9 additions & 7 deletions sklearn/decomposition/_dict_learning.py
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Expand Up @@ -511,7 +511,7 @@ def dict_learning(
positive_code=False,
method_max_iter=1000,
):
"""Solves a dictionary learning matrix factorization problem.
"""Solve a dictionary learning matrix factorization problem.

Finds the best dictionary and the corresponding sparse code for
approximating the data matrix X by solving::
Expand Down Expand Up @@ -567,7 +567,7 @@ def dict_learning(
if `code_init` and `dict_init` are not None.

callback : callable, default=None
Callable that gets invoked every five iterations
Callable that gets invoked every five iterations.

verbose : bool, default=False
To control the verbosity of the procedure.
Expand Down Expand Up @@ -612,11 +612,13 @@ def dict_learning(

See Also
--------
dict_learning_online
DictionaryLearning
MiniBatchDictionaryLearning
SparsePCA
MiniBatchSparsePCA
dict_learning_online : Solve a dictionary learning matrix factorization
problem online.
DictionaryLearning : Find a dictionary that sparsely encodes data.
MiniBatchDictionaryLearning : A faster, less accurate version
of the dictionary learning algorithm.
SparsePCA : Sparse Principal Components Analysis.
MiniBatchSparsePCA : Mini-batch Sparse Principal Components Analysis.
"""
if method not in ("lars", "cd"):
raise ValueError("Coding method %r not supported as a fit algorithm." % method)
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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -12,7 +12,6 @@
numpydoc_validation = pytest.importorskip("numpydoc.validate")

FUNCTION_DOCSTRING_IGNORE_LIST = [
"sklearn.decomposition._dict_learning.dict_learning",
"sklearn.externals._packaging.version.parse",
"sklearn.inspection._plot.partial_dependence.plot_partial_dependence",
"sklearn.linear_model._least_angle.lars_path_gram",
Expand Down