[jira] [Assigned] (SPARK-14604) Modify design of ML model summaries

["Joseph K. Bradley (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-14604?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley reassigned SPARK-14604:
-----------------------------------------

    Assignee: Joseph K. Bradley

> Modify design of ML model summaries
> -----------------------------------
>
>                 Key: SPARK-14604
>                 URL: https://issues.apache.org/jira/browse/SPARK-14604
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Assignee: Joseph K. Bradley
>
> 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.
> * 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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