Details

    • Type: Sub-task
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 1.5.2
    • Fix Version/s: 1.6.0, 2.0.0
    • Component/s: Documentation
    • Labels:
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    • Target Version/s:

      Description

      There is a confusion in the documentation of MLLib as to what exactly MLlib: is it the package, or is it the whole effort of ML on spark, and how it differs from spark.ml? Is MLLib going to be deprecated?

      We should do the following:

      • refer to the mllib the code package as spark.mllib across all the documentation. Alternative name is "RDD API of MLlib".
      • refer to MLlib the project that encompasses spark.ml + spark.mllib as MLlib (it should be the default)
      • replaces reference to "Pipeline API" by spark.ml or the "Dataframe API of MLlib". I would deemphasize that this API is for building pipelines. Some users are lead to believe from the documentation that spark.ml can only be used for building pipelines and that using a single algorithm can only be done with spark.mllib.

      Most relevant places:

      • mllib-guide.md
      • mllib-linear-methods.md
      • mllib-dimensionality-reduction.md
      • mllib-pmml-model-export.md
      • mllib-statistics.md
        In these files, most references to MLlib are meant to refer to spark.mllib instead.

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            • Assignee:
              timhunter Timothy Hunter
              Reporter:
              timhunter Timothy Hunter
              Shepherd:
              Joseph K. Bradley
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