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https://issues.apache.org/jira/browse/SPARK-10026?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-10026:
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Assignee: 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
> Assignee: Apache Spark
>
> 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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