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  1. Spark
  2. SPARK-19535

ALSModel recommendAll analogs

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Details

    • New Feature
    • Status: Resolved
    • Major
    • Resolution: Fixed
    • 2.2.0
    • 2.2.0
    • ML
    • None

    Description

      Add methods analogous to the spark.mllib MatrixFactorizationModel methods recommendProductsForUsers/UsersForProducts.

      The initial implementation should be very simple, using DataFrame joins. Future work can add optimizations.

      I recommend naming them:

      • recommendForAllUsers
      • recommendForAllItems

      Attachments

        Issue Links

          relates to

          Sub-task - The sub-task of the issue SPARK-13857 Feature parity for ALS ML with MLLIB

          • Major - Major loss of function.
          • Closed

          New Feature - A new feature of the product, which has yet to be developed. SPARK-20300 Python API for ALSModel.recommendForAllUsers,Items

          • Major - Major loss of function.
          • Resolved

          Improvement - An improvement or enhancement to an existing feature or task. SPARK-10802 Let ALS recommend for subset of data

          • Minor - Minor loss of function, or other problem where easy workaround is present.
          • Resolved

          Documentation - Documentation or Website SPARK-20553 Update ALS examples for ML to illustrate recommend all

          • Minor - Minor loss of function, or other problem where easy workaround is present.
          • Resolved
          links to

          Pull request #17090 [Github] Pull Request #17090 (sueann)

          Activity

            People

              sueann Sue Ann Hong
              josephkb Joseph K. Bradley
              Joseph K. Bradley Joseph K. Bradley
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              Dates

                Created:
                Updated:
                Resolved: