[
https://issues.apache.org/jira/browse/SPARK-12566?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15182384#comment-15182384
]
yuhao yang commented on SPARK-12566:
------------------------------------
Since we already have a glm in SparkR which is based on LogisticRegressionModel
and LinearRegressionModel. There're three ways to extend it as I understand:
1. Change the current glm to use GeneralizedLinearRegression. Create another lm
interface for sparkR, and use LR as the model.
2. Keep glm R interface. and replace its implementation with GLM. This means R
can not invoke LR anymore.
2. Keep glm R interface, and combine the implementation with both LR and GLM
based on different solver parameter.
I'd prefer to use option 1. And I'm gonna send one PR(WIP) for solution 2,
which can later be adjusted to 1 or 3.
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
