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  1. Spark
  2. SPARK-1548

Add Partial Random Forest algorithm to MLlib

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Details

    • New Feature
    • Status: Resolved
    • Major
    • Resolution: Incomplete
    • 1.0.0
    • None
    • MLlib

    Description

      This task involves creating an alternate approximate random forest implementation where each tree is constructed per partition.

      The tasks involves:

      • Justifying with theory and experimental results why this algorithm is a good choice.
      • Comparing the various tradeoffs and finalizing the algorithm before implementation
      • Code implementation
      • Unit tests
      • Functional tests
      • Performance tests
      • Documentation

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        is required by

        Improvement - An improvement or enhancement to an existing feature or task. SPARK-3703 Ensemble learning methods

        • Major - Major loss of function.
        • Resolved

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            Unassigned Unassigned Assign to me
            manishamde Manish Amde
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