From 369b6a9434f776ecc4281aabda2db376066d64b8 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Date: Thu, 30 Mar 2017 21:44:17 +0200
Subject: [PATCH] [MRG+1] DOC remove repetition in the Pipeline/memory doc
(#8669)
* DOC remove repetition in the Pipeline/memory doc
* DOC fix comments loic
---
sklearn/pipeline.py | 18 ++++++++----------
1 file changed, 8 insertions(+), 10 deletions(-)
diff --git a/sklearn/pipeline.py b/sklearn/pipeline.py
index 6dfc7284cc..0361e10901 100644
--- a/sklearn/pipeline.py
+++ b/sklearn/pipeline.py
@@ -110,16 +110,14 @@ class Pipeline(_BasePipeline):
an estimator.
memory : Instance of joblib.Memory or string, optional (default=None)
- Used to caching the fitted transformers of the transformer of the
- pipeline. By default, no cache is performed.
- If a string is given, it is the path to the caching directory.
- Enabling caching triggers a clone of the transformers before fitting.
- Therefore, the transformer instance given to the pipeline cannot be
- inspected directly. Use the attribute ``named_steps`` or ``steps``
- to inspect estimators within the pipeline.
- Caching the transformers is advantageous when fitting is time
- consuming.
-
+ Used to cache the fitted transformers of the pipeline. By default,
+ no caching is performed. If a string is given, it is the path to
+ the caching directory. Enabling caching triggers a clone of
+ the transformers before fitting. Therefore, the transformer
+ instance given to the pipeline cannot be inspected
+ directly. Use the attribute ``named_steps`` or ``steps`` to
+ inspect estimators within the pipeline. Caching the
+ transformers is advantageous when fitting is time consuming.
Attributes
----------
--
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