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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/04/07 01:47:25 UTC
[jira] [Commented] (SPARK-12566) GLM model family, link function
support in SparkR:::glm
[ https://issues.apache.org/jira/browse/SPARK-12566?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15229368#comment-15229368 ]
Joseph K. Bradley commented on SPARK-12566:
-------------------------------------------
Here's my preferred design. I prefer to abstract the implementation (solver) from the API (model) as much as possible.
* R glm calls Scala GLM, using solver = auto by default
* Scala GLM has solver = auto by default. Auto should mean "best effort"
** With few features (< 4K or so),
*** For family = gaussian and link = identity, use normal equations.
*** For others, use IRLS.
** With many features, use LBFGS if possible (for family, link). Otherwise, throw an exception.
* Scala LinearRegression, LogisticRegression call GLM. I.e., they uses normal equations, IRLS when possible.
What do yall think?
> 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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