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  1. Spark
  2. SPARK-7409

Designing multilabel abstractions for spark.ml

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Details

    • Brainstorming
    • Status: Resolved
    • Major
    • Resolution: Incomplete
    • None
    • None
    • ML

    Description

      This JIRA is for discussing how to support multi-label prediction in the Pipelines API (spark.ml package). Some issues to figure out are:

      • Should there be abstractions?
        • How should they relate to the existing single-label abstractions: Predictor, Classifier, Regressor?
        • How much code sharing can the abstractions provide?
      • How should we support a mix of categorical and real-valued labels?
      • How do we support structure among the labels? There could be no known structure, a graphical structure, a chain structure, etc., depending on the application/model.

      Attachments

        Issue Links

          Is contained by

          Umbrella - An overarching type made of sub-tasks SPARK-10817 ML abstraction umbrella

          • Major - Major loss of function.
          • Resolved
          is related to

          New Feature - A new feature of the product, which has yet to be developed. SPARK-7129 Add generic boosting algorithm to spark.ml

          • Major - Major loss of function.
          • Resolved

          New Feature - A new feature of the product, which has yet to be developed. SPARK-7128 Add generic bagging algorithm to spark.ml

          • Major - Major loss of function.
          • Closed

          Activity

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              Unassigned Unassigned
              josephkb Joseph K. Bradley
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              Dates

                Created:
                Updated:
                Resolved: