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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-10026) Implement some common Params for regression in PySpark
Date Fri, 28 Aug 2015 12:55:46 GMT

     [ https://issues.apache.org/jira/browse/SPARK-10026?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-10026:
------------------------------------

    Assignee:     (was: Apache Spark)

> Implement some common Params for regression in PySpark
> ------------------------------------------------------
>
>                 Key: SPARK-10026
>                 URL: https://issues.apache.org/jira/browse/SPARK-10026
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML, PySpark
>            Reporter: Yanbo Liang
>
> Currently some Params are not common classes in Python API which lead we need to write
them for each class. The LinearRegression and LogisticRegression related Params are list here:
> * HasElasticNetParam
> * HasFitIntercept
> * HasStandardization
> We should implement them in shared params and make them can be used for all Transformer/Estimators.
That will lead code more clean.



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