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https://issues.apache.org/jira/browse/SPARK-14604?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15253029#comment-15253029
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Joseph K. Bradley commented on SPARK-14604:
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It would be fine to add evaluate methods to the other models, but in a separate
PR.
No summary should provide the model.
> 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
>
> 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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