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  1. Spark
  2. SPARK-3770

The userFeatures RDD from MatrixFactorizationModel isn't accessible from the python bindings

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Details

    • Improvement
    • Status: Resolved
    • Major
    • Resolution: Fixed
    • None
    • 1.2.0
    • MLlib, PySpark
    • None

    Description

      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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            mdagost Michelangelo D'Agostino
            mdagost Michelangelo D'Agostino
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              Updated:
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