[MRG] Fix docstrings to Numpy format for `LabelBinarizer` #15440 #15460

paoloturati · 2019-11-02T16:59:02Z

Reference Issues/PRs

Contribution to fix part of #15440

What does this implement/fix? Explain your changes.

Ensuring LabelBinarizer methods pass NumPy docstring validation

labelBin: fixed docstring

…into labelBin

TomDLT · 2019-11-02T17:02:48Z

Please mention the issue you are addressing, in this case #15440 I guess.
This is easier for reviewers to understand why you did your pull-request.
I just noted that you mentioned the issue, but you wrote it inside comments brackets , so it was not displayed. I edited your message.

TomDLT · 2019-11-02T17:08:05Z

sklearn/base.py

-        Fits transformer to X and y with optional parameters fit_params
-        and returns a transformed version of X.
+        """
+        Fit to data, then transform it. Fits transformer to X and y with


I think it is better rendered if you have a short title first (Fit to data, then transform it), then an empty line, then a more detailed description.

TomDLT · 2019-11-02T17:12:36Z

sklearn/preprocessing/_label.py

-            represents multilabel classification. Sparse matrix can be
-            CSR, CSC, COO, DOK, or LIL.
+        y : array or sparse matrix of shape [n_samples,] or
+            [n_samples, n_classes]. Target values. The 2-d matrix


Not sure it will be rendered correctly on the website.
I need to wait for the doc build to complete to check it.

you need a break line

glemaitre

A couple of changes

glemaitre · 2019-11-02T19:21:45Z

sklearn/base.py

@@ -172,7 +172,7 @@ def get_params(self, deep=True):

        Parameters
        ----------
-        deep : bool, default=True
+        deep : bool, optional


You should keep default=True

glemaitre · 2019-11-02T19:21:54Z

sklearn/base.py

@@ -435,20 +435,21 @@ class ClusterMixin:
    _estimator_type = "clusterer"

    def fit_predict(self, X, y=None):
-        """Performs clustering on X and returns cluster labels.
+        """
+        Performs clustering on X and returns cluster labels.


Suggested change

Performs clustering on X and returns cluster labels.

Perform clustering on X and returns cluster labels.

glemaitre · 2019-11-02T19:22:03Z

sklearn/base.py

@@ -435,20 +435,21 @@ class ClusterMixin:
    _estimator_type = "clusterer"

    def fit_predict(self, X, y=None):
-        """Performs clustering on X and returns cluster labels.
+        """
+        Performs clustering on X and returns cluster labels.

        Parameters
        ----------
        X : ndarray, shape (n_samples, n_features)
            Input data.

        y : Ignored


Suggested change

y : Ignored

y : None

glemaitre · 2019-11-02T19:22:57Z

sklearn/preprocessing/_label.py

-
-    sklearn.preprocessing.OneHotEncoder : Encode categorical features
-        as a one-hot numeric array.
+    ['tokyo', 'tokyo', 'paris'].


This will fail. You should not a full stop. This is part of the examples

glemaitre · 2019-11-02T19:23:12Z

sklearn/preprocessing/_label.py

@@ -244,14 +247,15 @@ def fit_transform(self, y):

        Returns
        -------
-        y : array-like of shape [n_samples]
+        y : array-like of shape [n_samples].


Suggested change

y : array-like of shape [n_samples].

y : array-like of shape (n_samples,)

glemaitre · 2019-11-02T19:25:40Z

sklearn/preprocessing/_label.py

@@ -561,14 +575,19 @@ def label_binarize(y, classes, neg_label=0, pos_label=1, sparse_output=False):
    pos_label : int (default: 1)
        Value with which positive labels must be encoded.

-    sparse_output : boolean (default: False),
+    sparse_output : bool (default: False),


Suggested change

sparse_output : bool (default: False),

sparse_output : bool, default=False

glemaitre · 2019-11-02T19:25:55Z

sklearn/preprocessing/_label.py

-    --------
-    LabelBinarizer : class used to wrap the functionality of label_binarize and
-        allow for fitting to classes independently of the transform operation
+           [1]]).


Suggested change

[1]]).

[1]])

Part of the example

glemaitre · 2019-11-02T19:26:08Z

sklearn/preprocessing/_label.py

@@ -798,7 +815,7 @@ class MultiLabelBinarizer(TransformerMixin, BaseEstimator):
        Indicates an ordering for the class labels.
        All entries should be unique (cannot contain duplicate classes).

-    sparse_output : boolean (default: False),
+    sparse_output : bool (default: False),


Suggested change

sparse_output : bool (default: False),

sparse_output : bool, default=False

glemaitre · 2019-11-02T19:26:23Z

sklearn/preprocessing/_label.py

-    --------
-    sklearn.preprocessing.OneHotEncoder : encode categorical features
-        using a one-hot aka one-of-K scheme.
+    array(['comedy', 'sci-fi', 'thriller'], dtype=object).


Suggested change

array(['comedy', 'sci-fi', 'thriller'], dtype=object).

array(['comedy', 'sci-fi', 'thriller'], dtype=object)

Part of the example

glemaitre · 2019-11-02T19:27:07Z

sklearn/preprocessing/_label.py

@@ -966,7 +988,7 @@ def _transform(self, y, class_mapping):
        Returns
        -------
        y_indicator : sparse CSR matrix, shape (n_samples, n_classes)


Suggested change

y_indicator : sparse CSR matrix, shape (n_samples, n_classes)

y_indicator : sparse matrix of shape (n_samples, n_classes)

cmarmo · 2021-11-05T20:51:21Z

Referencing here #21350 as this PR addressed it.

jeremiedbb · 2022-03-21T21:15:52Z

done as part of #20308. Thanks @paoloturati

paoloturati added 6 commits November 2, 2019 12:27

labelBin: fixed docstring LabelBinarizer

3d7e86b

labelBin: fixed docstring

dac9dbd

labelBin: fixed docstring LabelBinarizer

2db95b8

labelBin: fixed docstring

Merge branch 'labelBin' of https://github.com/gbroccolo/scikit-learn …

831c799

…into labelBin

labelBin: fixed docstring

928ca37

labelBin: fixed docstring

7d56087

TomDLT reviewed Nov 2, 2019

View reviewed changes

TomDLT added the Documentation label Nov 2, 2019

glemaitre reviewed Nov 2, 2019

View reviewed changes

paoloturati and others added 2 commits November 8, 2019 00:05

labelBin: fixed conflicts on PR

d8b1102

Merge branch 'master' into labelBin

1420191

github-actions bot added the module:preprocessing label Mar 2, 2020

Base automatically changed from master to main January 22, 2021 10:51

cmarmo added help wanted Stalled labels Jan 4, 2022

jeremiedbb closed this Mar 21, 2022

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[MRG] Fix docstrings to Numpy format for `LabelBinarizer` #15440 #15460

[MRG] Fix docstrings to Numpy format for `LabelBinarizer` #15440 #15460

paoloturati commented Nov 2, 2019 •

edited by TomDLT

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TomDLT commented Nov 2, 2019 •

edited

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cmarmo commented Nov 5, 2021

jeremiedbb commented Mar 21, 2022

	Performs clustering on X and returns cluster labels.
	Perform clustering on X and returns cluster labels.

	y : array-like of shape [n_samples].
	y : array-like of shape (n_samples,)

	sparse_output : bool (default: False),
	sparse_output : bool, default=False

	array(['comedy', 'sci-fi', 'thriller'], dtype=object).
	array(['comedy', 'sci-fi', 'thriller'], dtype=object)

	y_indicator : sparse CSR matrix, shape (n_samples, n_classes)
	y_indicator : sparse matrix of shape (n_samples, n_classes)

[MRG] Fix docstrings to Numpy format for LabelBinarizer #15440 #15460

[MRG] Fix docstrings to Numpy format for LabelBinarizer #15440 #15460

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paoloturati commented Nov 2, 2019 • edited by TomDLT Loading

Reference Issues/PRs

What does this implement/fix? Explain your changes.

TomDLT commented Nov 2, 2019 • edited Loading

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cmarmo commented Nov 5, 2021

jeremiedbb commented Mar 21, 2022

[MRG] Fix docstrings to Numpy format for `LabelBinarizer` #15440 #15460

[MRG] Fix docstrings to Numpy format for `LabelBinarizer` #15440 #15460

paoloturati commented Nov 2, 2019 •

edited by TomDLT

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TomDLT commented Nov 2, 2019 •

edited

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