8000 DOC - Ensure HuberRegressor passes numpydoc validation by EricEllwanger · Pull Request #21062 · scikit-learn/scikit-learn · GitHub
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DOC - Ensure HuberRegressor passes numpydoc validation #21062

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Merged
merged 11 commits into from
Sep 17, 2021
Merged

DOC - Ensure HuberRegressor passes numpydoc validation #21062

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7efe8aa
(#20308) HuberRegressor changed order of sections
frellwan Sep 16, 2021
77fe78a
(#20308) HuberRegressor added 'See Also' section
frellwan Sep 16, 2021
c03f307
(#20308) HuberRegressor.fit added 'Returns' description
frellwan Sep 16, 2021
8ba5c83
(#20308) Removed HuberRegressor from DOCSTRING_IGNORE_LIST
frellwan Sep 16, 2021
96ab359
Update sklearn/linear_model/_huber.py
EricEllwanger Sep 16, 2021
8795429
(#20308) Updated with suggestions
frellwan Sep 16, 2021
94f29cb
Merge branch 'main' of https://github.com/scikit-learn/scikit-learn i…
frellwan Sep 16, 2021
d6b16cf
Update _huber.py
EricEllwanger Sep 16, 2021
eb8599f
Update _huber.py
EricEllwanger Sep 16, 2021
779db3d
(#20308) Added Period
frellwan Sep 17, 2021
a583d53
Update sklearn/linear_model/_huber.py
glemaitre Sep 17, 2021
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1 change: 0 additions & 1 deletion maint_tools/test_docstrings.py
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Expand Up @@ -9,7 +9,6 @@

# List of modules ignored when checking for numpydoc validation.
DOCSTRING_IGNORE_LIST = [
"HuberRegressor",
"IterativeImputer",
"KNNImputer",
"LabelPropagation",
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21 changes: 14 additions & 7 deletions sklearn/linear_model/_huber.py
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Expand Up @@ -205,6 +205,19 @@ class HuberRegressor(LinearModel, RegressorMixin, BaseEstimator):
A boolean mask which is set to True where the samples are identified
as outliers.

See Also
--------
RANSACRegressor : RANSAC (RANdom SAmple Consensus) algorithm.
TheilSenRegressor : Theil-Sen Estimator robust multivariate regression model.
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Could you add the SGDRegressor as well. This estimator can get several loss functions as the Huber loss as well.

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It should be added now

SGDRegressor : Fitted by minimizing a regularized empirical loss with SGD.

References
----------
.. [1] Peter J. Huber, Elvezio M. Ronchetti, Robust Statistics
Concomitant scale estimates, pg 172
.. [2] Art B. Owen (2006), A robust hybrid of lasso and ridge regression.
https://statweb.stanford.edu/~owen/reports/hhu.pdf

Examples
--------
>>> import numpy as np
Expand All @@ -227,13 +240,6 @@ class HuberRegressor(LinearModel, RegressorMixin, BaseEstimator):
Huber coefficients: [17.7906... 31.0106...]
>>> print("Linear Regression coefficients:", linear.coef_)
Linear Regression coefficients: [-1.9221... 7.0226...]

References
----------
.. [1] Peter J. Huber, Elvezio M. Ronchetti, Robust Statistics
Concomitant scale estimates, pg 172
.. [2] Art B. Owen (2006), A robust hybrid of lasso and ridge regression.
https://statweb.stanford.edu/~owen/reports/hhu.pdf
"""

def __init__(
Expand Down Expand Up @@ -271,6 +277,7 @@ def fit(self, X, y, sample_weight=None):
Returns
-------
self : object
Fitted `HuberRegressor` estimator.
"""
X, y = self._validate_data(
X,
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0