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  1. PUBDEV-3743

StackedEnsemble should allow user to pass in metalearner type

    Details

    • Type: New Feature
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: 3.16.0.1
    • Component/s: StackedEnsemble
    • Labels:
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      Description

      • Currently the metalearner is hardcoded as a default H2O GLM with non-negative weights. (`non_negative = TRUE`)
      • We need to add a `metalearner_algorithm` argument to allow customization of the metalearning algorithm.
        Initially, this argument will take in either "glm" (default), "gbm", "drf", or "deeplearning".
      • A user cannot specify the metalearner model hyperparameters at this point. This will be completed with the addition of another argument, e.g. `metalearner_params`
      • junit, runit, pyunit for this argument is included

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              • Assignee:
                navdeep Navdeep
                Reporter:
                erin Erin LeDell
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                • Created:
                  Updated:
                  Resolved: