You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:34:54 UTC

[jira] [Resolved] (SPARK-6823) Add a model.matrix like capability to DataFrames (modelDataFrame)

     [ https://issues.apache.org/jira/browse/SPARK-6823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-6823.
---------------------------------
    Resolution: Incomplete

> Add a model.matrix like capability to DataFrames (modelDataFrame)
> -----------------------------------------------------------------
>
>                 Key: SPARK-6823
>                 URL: https://issues.apache.org/jira/browse/SPARK-6823
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML, SparkR
>            Reporter: Shivaram Venkataraman
>            Priority: Major
>              Labels: bulk-closed
>
> Currently Mllib modeling tools work only with double data. However, data tables in practice often have a set of categorical fields (factors in R), that need to be converted to a set of 0/1 indicator variables (making the data actually used in a modeling algorithm completely numeric). In R, this is handled in modeling functions using the model.matrix function. Similar functionality needs to be available within Spark.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org