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  1. Machine Learning Library
  2. ML-363

Common critical data check approach and diagnostic

    Details

    • Type: Improvement
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: 6.4.2
    • Component/s: ML_Core
    • Labels:
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      Description

      There may be critical data requirements in ML or Stats processes and or implementations.  For example, it is an error for the response (dependent) variable in a Binomial Regression to have either 1 value or more than two values.  With respect to algorithms, there may be implementation restrictions such as dense columns or dense rows (no gaps).

      There will be a standard diagnostic layout:

      Data_Diagnostic := RECORD
        t_work_item wi;
        BOOLEAN valid;
        ARRAY OF STRING message_text;
      END;

      Each component that has firm data requirements will use an ASSERT to produce either a Warning or a Fail (depending) message that informs the user to run this report.

      Each component will need a separate Jira, which should be dependent upon this Jira.

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              • Assignee:
                timothyesler Tim Esler
                Reporter:
                johnholt John Holt
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                • Created:
                  Updated:
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