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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-28159) Make the transform natively in ml framework to avoid extra conversion
Date Mon, 08 Jul 2019 19:47:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-28159?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Sean Owen resolved SPARK-28159.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 3.0.0

Issue resolved by pull request 24963
[https://github.com/apache/spark/pull/24963]

> Make the transform natively in ml framework to avoid extra conversion
> ---------------------------------------------------------------------
>
>                 Key: SPARK-28159
>                 URL: https://issues.apache.org/jira/browse/SPARK-28159
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Assignee: zhengruifeng
>            Priority: Major
>             Fix For: 3.0.0
>
>
> It is a long time since ML was released.
> However, there are still many TODOs (like in [ChiSqSelector.scala|https://github.com/apache/spark/pull/24963/files#diff-9b0bc8a01b34c38958ce45c14f9c5da5]
{// TODO: Make the transformer natively in ml framework to avoid extra conversion.}) on making
transform natively in ml framework.
>  
> I try to make ml algs no longer need to convert ml-vector to mllib-vector in transforms.
> Including: LDA/ChiSqSelector/ElementwiseProduct/HashingTF/IDF/Normalizer/PCA/StandardScaler.
>  



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