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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2015/09/11 17:51:46 UTC

[jira] [Updated] (SPARK-10026) Implement some common Params for regression in PySpark

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

Xiangrui Meng updated SPARK-10026:
----------------------------------
    Target Version/s: 1.6.0

> 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
>            Assignee: Yanbo Liang
>             Fix For: 1.6.0
>
>
> 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
> * HasThresholds
> 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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