From ee7f05a653c90f4cf912d434302597f16edb75a2 Mon Sep 17 00:00:00 2001 From: Hanmin Qin Date: Sun, 27 Jan 2019 16:46:07 +0800 Subject: [PATCH] DOC Remove outdated doc in KBinsDiscretizer --- sklearn/preprocessing/_discretization.py | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/sklearn/preprocessing/_discretization.py b/sklearn/preprocessing/_discretization.py index b57e03230f4f1..cba2ebb9bd5a2 100644 --- a/sklearn/preprocessing/_discretization.py +++ b/sklearn/preprocessing/_discretization.py @@ -27,12 +27,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin): Parameters ---------- n_bins : int or array-like, shape (n_features,) (default=5) - The number of bins to produce. The intervals for the bins are - determined by the minimum and maximum of the input data. - Raises ValueError if ``n_bins < 2``. - - If ``n_bins`` is an array, and there is an ignored feature at - index ``i``, ``n_bins[i]`` will be ignored. + The number of bins to produce. Raises ValueError if ``n_bins < 2``. encode : {'onehot', 'onehot-dense', 'ordinal'}, (default='onehot') Method used to encode the transformed result. @@ -62,8 +57,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin): Attributes ---------- n_bins_ : int array, shape (n_features,) - Number of bins per feature. An ignored feature at index ``i`` - will have ``n_bins_[i] == 0``. + Number of bins per feature. bin_edges_ : array of arrays, shape (n_features, ) The edges of each bin. Contain arrays of varying shapes ``(n_bins_, )``