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DOC Ensures that OrthogonalMatchingPursuitCV passes numpydoc validation #21412

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Oct 23, 2021
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DOC Ensures that OrthogonalMatchingPursuitCV passes numpydoc validation #21412

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1 change: 0 additions & 1 deletion maint_tools/test_docstrings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,6 @@
DOCSTRING_IGNORE_LIST = [
"LabelSpreading",
"MultiTaskElasticNetCV",
"OrthogonalMatchingPursuitCV",
"PassiveAggressiveRegressor",
"SpectralCoclustering",
"SpectralEmbedding",
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31 changes: 16 additions & 15 deletions sklearn/linear_model/_omp.py
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Expand Up @@ -880,7 +880,7 @@ class OrthogonalMatchingPursuitCV(RegressorMixin, LinearModel):
copy is made anyway.

fit_intercept : bool, default=True
whether to calculate the intercept for this model. If set
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations
(i.e. data is expected to be centered).

Expand Down Expand Up @@ -953,6 +953,20 @@ class OrthogonalMatchingPursuitCV(RegressorMixin, LinearModel):

.. versionadded:: 1.0

See Also
--------
orthogonal_mp : Solves n_targets Orthogonal Matching Pursuit problems.
orthogonal_mp_gram : Solves n_targets Orthogonal Matching Pursuit
problems using only the Gram matrix X.T * X and the product X.T * y.
lars_path : Compute Least Angle Regression or Lasso path using LARS algorithm.
Lars : Least Angle Regression model a.k.a. LAR.
LassoLars : Lasso model fit with Least Angle Regression a.k.a. Lars.
OrthogonalMatchingPursuit : Orthogonal Matching Pursuit model (OMP).
LarsCV : Cross-validated Least Angle Regression model.
LassoLarsCV : Cross-validated Lasso model fit with Least Angle Regression.
sklearn.decomposition.sparse_encode : Generic sparse coding.
Each column of the result is the solution to a Lasso problem.

Examples
--------
>>> from sklearn.linear_model import OrthogonalMatchingPursuitCV
Expand All @@ -966,19 +980,6 @@ class OrthogonalMatchingPursuitCV(RegressorMixin, LinearModel):
10
>>> reg.predict(X[:1,])
array([-78.3854...])

See Also
--------
orthogonal_mp
orthogonal_mp_gram
lars_path
Lars
LassoLars
OrthogonalMatchingPursuit
LarsCV
LassoLarsCV
sklearn.decomposition.sparse_encode

"""

def __init__(
Expand Down Expand Up @@ -1014,7 +1015,7 @@ def fit(self, X, y):
Returns
-------
self : object
returns an instance of self.
Returns an instance of self.
"""

_normalize = _deprecate_normalize(
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