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  1. Spark
  2. SPARK-9904

User guide for ML tree algorithms

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Details

    • Documentation
    • Status: Closed
    • Major
    • Resolution: Duplicate
    • None
    • None
    • ML
    • None

    Description

      The ML Pipeline implementation of trees has diverged sufficiently from MLlib to warrant it's own user guide. Notable features which only exist in ML include:

      We should add a new section to ml-guide#algorithm-guides to describe trees in ML pipeline

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        is related to

        Sub-task - The sub-task of the issue SPARK-6885 Decision trees: predict class probabilities

        • Major - Major loss of function.
        • Resolved

        Sub-task - The sub-task of the issue SPARK-6884 Random forest: predict class probabilities

        • Major - Major loss of function.
        • Closed

        New Feature - A new feature of the product, which has yet to be developed. SPARK-5133 Feature Importance for Random Forests

        • Major - Major loss of function.
        • Resolved

        Improvement - An improvement or enhancement to an existing feature or task. SPARK-6684 Add checkpointing to GradientBoostedTrees

        • Major - Major loss of function.
        • Resolved

        Improvement - An improvement or enhancement to an existing feature or task. SPARK-8069 Add support for cutoff to RandomForestClassifier

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

        Documentation - Documentation or Website SPARK-7772 User guide for spark.ml trees and ensembles

        • Major - Major loss of function.
        • Resolved
        is required by

        Sub-task - The sub-task of the issue SPARK-9668 ML 1.5 QA: Docs: Check for new APIs

        • Major - Major loss of function.
        • Resolved

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            Unassigned Unassigned
            fliang Feynman Liang
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              Updated:
              Resolved:

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