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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2014/10/21 23:20:35 UTC
[jira] [Updated] (SPARK-3770) The userFeatures RDD from
MatrixFactorizationModel isn't accessible from the python bindings
[ https://issues.apache.org/jira/browse/SPARK-3770?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng updated SPARK-3770:
---------------------------------
Assignee: Michelangelo D'Agostino
> The userFeatures RDD from MatrixFactorizationModel isn't accessible from the python bindings
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-3770
> URL: https://issues.apache.org/jira/browse/SPARK-3770
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Reporter: Michelangelo D'Agostino
> Assignee: Michelangelo D'Agostino
>
> 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 fixed this with a PR that I'll submit shortly that adds 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
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