[jira] [Commented] (SPARK-1227) Diagnostics for Classification&Regression

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

    [ https://issues.apache.org/jira/browse/SPARK-1227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14491895#comment-14491895 ] 

Joseph K. Bradley commented on SPARK-1227:
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I agree it will be nice to provide loss classes.  Even though *Metrics classes exist already, loss classes might be nice as we provide more functionality for diagnosis during learning (e.g., for early stopping, model selection, etc.).  Added link to related JIRA on optimization APIs.

> Diagnostics for Classification&Regression
> -----------------------------------------
>
>                 Key: SPARK-1227
>                 URL: https://issues.apache.org/jira/browse/SPARK-1227
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>            Reporter: Martin Jaggi
>            Assignee: Martin Jaggi
>
> Currently, the attained objective function is not computed (for efficiency reasons, as one evaluation requires one full pass through the data).
> For diagnostics and comparing different algorithms, we should however provide this as a separate function (one MR).
> Doing this requires the loss and regularizer functions themselves, not only their gradients (which are currently in the Gradient class). How about adding the new function directly on the corresponding models in classification/* and regression/* ? Any thoughts?



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