8000 DOC Remove outdated doc in KBinsDiscretizer (#13047) · scikit-learn/scikit-learn@025cff2 · GitHub
[go: up one dir, main page]

Skip to content

Commit 025cff2

Browse files
qinhanmin2014jnothman
authored andcommitted
DOC Remove outdated doc in KBinsDiscretizer (#13047)
1 parent 60be46c commit 025cff2

File tree

1 file changed

+2
-8
lines changed

1 file changed

+2
-8
lines changed

sklearn/preprocessing/_discretization.py

Lines changed: 2 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -27,12 +27,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin):
2727
Parameters
2828
----------
2929
n_bins : int or array-like, shape (n_features,) (default=5)
30-
The number of bins to produce. The intervals for the bins are
31-
determined by the minimum and maximum of the input data.
32-
Raises ValueError if ``n_bins < 2``.
33-
34-
If ``n_bins`` is an array, and there is an ignored feature at
35-
index ``i``, ``n_bins[i]`` will be ignored.
30+
The number of bins to produce. Raises ValueError if ``n_bins < 2``.
3631
3732
encode : {'onehot', 'onehot-dense', 'ordinal'}, (default='onehot')
3833
Method used to encode the transformed result.
@@ -62,8 +57,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin):
6257
Attributes
6358
----------
6459
n_bins_ : int array, shape (n_features,)
65-
Number of bins per feature. An ignored feature at index ``i``
66-
will have ``n_bins_[i] == 0``.
60+
Number of bins per feature.
6761
6862
bin_edges_ : array of arrays, shape (n_features, )
6963
The edges of each bin. Contain arrays of varying shapes ``(n_bins_, )``

0 commit comments

Comments
 (0)
0