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author | Sean Owen <sowen@cloudera.com> | 2016-08-27 08:48:56 +0100 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-08-27 08:48:56 +0100 |
commit | e07baf14120bc94b783649dabf5fffea58bff0de (patch) | |
tree | 557979925874c18034e793057a9706c3ee6924fa /python/pyspark/mllib | |
parent | 9fbced5b25c2f24d50c50516b4b7737f7e3eaf86 (diff) | |
download | spark-e07baf14120bc94b783649dabf5fffea58bff0de.tar.gz spark-e07baf14120bc94b783649dabf5fffea58bff0de.tar.bz2 spark-e07baf14120bc94b783649dabf5fffea58bff0de.zip |
[SPARK-17001][ML] Enable standardScaler to standardize sparse vectors when withMean=True
## What changes were proposed in this pull request?
Allow centering / mean scaling of sparse vectors in StandardScaler, if requested. This is for compatibility with `VectorAssembler` in common usages.
## How was this patch tested?
Jenkins tests, including new caes to reflect the new behavior.
Author: Sean Owen <sowen@cloudera.com>
Closes #14663 from srowen/SPARK-17001.
Diffstat (limited to 'python/pyspark/mllib')
-rw-r--r-- | python/pyspark/mllib/feature.py | 5 |
1 files changed, 2 insertions, 3 deletions
diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py index c8a6e33f4d..324ba9758e 100644 --- a/python/pyspark/mllib/feature.py +++ b/python/pyspark/mllib/feature.py @@ -208,9 +208,8 @@ class StandardScaler(object): training set. :param withMean: False by default. Centers the data with mean - before scaling. It will build a dense output, so this - does not work on sparse input and will raise an - exception. + before scaling. It will build a dense output, so take + care when applying to sparse input. :param withStd: True by default. Scales the data to unit standard deviation. |