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  1. Spark
  2. SPARK-14604

Modify design of ML model summaries

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    Details

    • Type: Improvement
    • Status: Resolved
    • Priority: Major
    • Resolution: Incomplete
    • Affects Version/s: None
    • Fix Version/s: None
    • Component/s: ML
    • Labels:

      Description

      Several spark.ml models now have summaries containing evaluation metrics and training info:

      • LinearRegressionModel
      • LogisticRegressionModel
      • GeneralizedLinearRegressionModel

      These summaries have unfortunately been added in an inconsistent way. I propose to reorganize them to have:

      • For each model, 1 summary (without training info) and 1 training summary (with info from training). The non-training summary can be produced for a new dataset via evaluate.
      • A summary should not store the model itself as a public field.
      • A summary should provide a transient reference to the dataset used to produce the summary.

      This task will involve reorganizing the GLM summary (which lacks a training/non-training distinction) and deprecating the model method in the LinearRegressionSummary.

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            • Assignee:
              Unassigned
              Reporter:
              josephkb Joseph K. Bradley
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