Michelangelo D'Agostino created SPARK-3770:
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Summary: 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
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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