GitHub user mdagost opened a pull request:
https://github.com/apache/spark/pull/2636
SPARK-3770: Make userFeatures accessible from python
https://issues.apache.org/jira/browse/SPARK-3770
We need access to the underlying latent user features from python. However,
the userFeatures RDD from the MatrixFactorizationModel isn't accessible from
the python bindings. I've added a method to the underlying scala class to turn
the RDD[(Int, Array[Double])] to an RDD[String]. This is then accessed from the
python recommendation.py
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mdagost/spark mf_user_features
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/2636.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 #2636
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commit e1fbe5e82a6b9436ce745175670cd005f6481173
Author: Michelangelo D'Agostino <[email protected]>
Date: 2014-10-02T13:33:45Z
Added scala function to stringify userFeatures for access in python.
commit cdd98e3a43cc465844a3b38432f4edc679ffa0dd
Author: Michelangelo D'Agostino <[email protected]>
Date: 2014-10-02T16:05:48Z
It's working now.
commit 34cb2a2889649e3f29f1686745320884f1fbc945
Author: Michelangelo D'Agostino <[email protected]>
Date: 2014-10-02T21:41:51Z
A couple of lint cleanups and a comment.
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