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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-16442) MLlib wrappers for SparkR 2.1
Date Fri, 08 Jul 2016 16:22:11 GMT

     [ https://issues.apache.org/jira/browse/SPARK-16442?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiangrui Meng reassigned SPARK-16442:
-------------------------------------

    Assignee: Xiangrui Meng

> MLlib wrappers for SparkR 2.1
> -----------------------------
>
>                 Key: SPARK-16442
>                 URL: https://issues.apache.org/jira/browse/SPARK-16442
>             Project: Spark
>          Issue Type: Umbrella
>          Components: MLlib, SparkR
>            Reporter: Xiangrui Meng
>            Assignee: Xiangrui Meng
>
> This is an umbrella JIRA to track MLlib wrappers in SparkR for the release 2.1. The wrappers
should follow existing implementations such as `spark.glm`, `spark.kmeans`, `spark.naiveBayes`,
etc. And the APIs should follow SPARK-14831:
> {code}
> spark.algo(data, formula, required params, [optional params])
> summary(object)
> predict(object, newData)
> write.ml(object, path, ...)
> {code}
> Implementation should also update `read.ml` to load the saved models back. Documentation
should follow SPARK-16090 and group the methods above into a single Rd.



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