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Posted to issues@spark.apache.org by "zhengruifeng (Jira)" <ji...@apache.org> on 2019/11/21 01:53:00 UTC

[jira] [Commented] (SPARK-29967) KMeans support instance weighting

    [ https://issues.apache.org/jira/browse/SPARK-29967?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16978897#comment-16978897 ] 

zhengruifeng commented on SPARK-29967:
--------------------------------------

[~srowen]   Hi, Owen how would you think of this ticket? If you feel OK, I guess we can working on making existing clustering algoritms support weight sample.

> KMeans support instance weighting
> ---------------------------------
>
>                 Key: SPARK-29967
>                 URL: https://issues.apache.org/jira/browse/SPARK-29967
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, PySpark
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Priority: Major
>
> Since https://issues.apache.org/jira/browse/SPARK-9610, we start to support instance weighting in ML.
> However, Clustering and other impl in features still do not support instance weighting.
> I think we need to start support weighting in KMeans, like what scikit-learn does.
> It will contains three parts:
> 1, move the impl from .mllib to .ml
> 2, make .mllib.KMeans as a wrapper of .ml.KMeans
> 3, support instance weighting in the .ml.KMeans



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