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https://issues.apache.org/jira/browse/SPARK-12566?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15188057#comment-15188057
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Timothy Hunter commented on SPARK-12566:
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[~yuhaoyan] I took a look at the current code, and it looks like the
implementation of GLM in SparkRWrappers, and it looks like we only check the
solver in the case of the gaussian family.
[~mengxr] if users use the 'auto' solver, it means we can swap the
implementation underneath, right?
If this is the case, here is what I suggest, in pseudo-scala-code:
{code}
(family, solver) match {
(gaussian, auto) => IRLS // This is a behavioral change
(gaussian, normal | l-bfgs) => LinearRegression
(binomial, auto) => IRLS // This is a behavioral change
(binomial, binomial) => LogisticRegression // This is a new option to
preserve logisticregression if there is a need for that
(_, _) => IRLS
}
{code}
> GLM model family, link function support in SparkR:::glm
> -------------------------------------------------------
>
> Key: SPARK-12566
> URL: https://issues.apache.org/jira/browse/SPARK-12566
> Project: Spark
> Issue Type: New Feature
> Components: ML, SparkR
> Reporter: Joseph K. Bradley
> Assignee: yuhao yang
> Priority: Critical
>
> This JIRA is for extending the support of MLlib's Generalized Linear Models
> (GLMs) to more model families and link functions in SparkR. After
> SPARK-12811, we should be able to wrap GeneralizedLinearRegression in SparkR
> with support of popular families and link functions.
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