GitHub user sryza opened a pull request:
https://github.com/apache/spark/pull/5500
SPARK-5888. [MLLIB]. Add OneHotEncoder as a Transformer
This patch adds a one hot encoder for categorical features. Planning to
add documentation and another test after getting feedback on the approach.
A couple choices made here:
* There's an `includeFirst` option which, if false, creates numCategories -
1 columns and, if true, creates numCategories columns. The default is true,
which is the behavior in scikit-learn.
* The user is expected to pass a `Seq` of category names when instantiating
a `OneHotEncoder`. These can be easily gotten from a `StringIndexer`. The
names are used for the output column names, which take the form
colName_categoryName.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/sryza/spark sandy-spark-5888
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/5500.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #5500
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commit 04590bc362d011cc92b7ca1e703c15e090805b71
Author: Sandy Ryza <[email protected]>
Date: 2015-04-13T23:40:04Z
SPARK-5888. [MLLIB]. Add OneHotEncoder as a Transformer
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