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[SPARK-7922] [MLLIB] use DataFrames for user/item factors in ALSModel
Expose user/item factors in DataFrames. This is to be more consistent with the pipeline API. It also helps maintain consistent APIs across languages. This PR also removed fitting params from `ALSModel`. coderxiang Author: Xiangrui Meng <meng@databricks.com> Closes #6468 from mengxr/SPARK-7922 and squashes the following commits: 7bfb1d5 [Xiangrui Meng] update ALSModel in PySpark 1ba5607 [Xiangrui Meng] use DataFrames for user/item factors in ALS
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- mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala 57 additions, 44 deletions...c/main/scala/org/apache/spark/ml/recommendation/ALS.scala
- python/pyspark/ml/recommendation.py 28 additions, 2 deletionspython/pyspark/ml/recommendation.py
- python/pyspark/mllib/common.py 4 additions, 1 deletionpython/pyspark/mllib/common.py
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