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DOC Ensures that IsotonicRegression passes numpydoc validation #20514

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Jul 20, 2021
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DOC Ensures that IsotonicRegression passes numpydoc validation #20514

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6330fbf
Remove IsotonicRegression from docstrings_ignore_list
embandera Jul 12, 2021
cda5f35
Ensure IsotonicRegression passes numpydoc validation
embandera Jul 12, 2021
1536227
apply suggestion ogrisel
glemaitre Jul 20, 2021
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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 @@ -55,7 +55,6 @@
"HuberRegressor",
"IncrementalPCA",
"Isomap",
"IsotonicRegression",
"IterativeImputer",
"KBinsDiscretizer",
"KNNImputer",
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12 changes: 10 additions & 2 deletions sklearn/isotonic.py
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Expand Up @@ -189,6 +189,14 @@ class IsotonicRegression(RegressorMixin, TransformerMixin, BaseEstimator):
increasing_ : bool
Inferred value for ``increasing``.

See Also
--------
sklearn.linear_model.LinearRegression : Ordinary least squares Linear
Regression.
sklearn.ensemble.HistGradientBoostingRegressor : Gradient boosting that
is a non-parametric model accepting monotonicity constraints.
isotonic_regression : Function to solve the isotonic regression model.

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Notes
-----
Ties are broken using the secondary method from de Leeuw, 1977.
Expand Down Expand Up @@ -348,7 +356,7 @@ def fit(self, X, y, sample_weight=None):
return self

def transform(self, T):
"""Transform new data by linear interpolation
"""Transform new data by linear interpolation.

Parameters
----------
Expand All @@ -361,7 +369,7 @@ def transform(self, T):
Returns
-------
y_pred : ndarray of shape (n_samples,)
The transformed data
The transformed data.
"""

if hasattr(self, "X_thresholds_"):
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