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Posted to issues@spark.apache.org by "Barry Becker (JIRA)" <ji...@apache.org> on 2018/08/15 15:41:00 UTC

[jira] [Commented] (SPARK-9610) Class and instance weighting for ML

    [ https://issues.apache.org/jira/browse/SPARK-9610?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16581253#comment-16581253 ] 

Barry Becker commented on SPARK-9610:
-------------------------------------

All ML models should support having and optional weighting column set. The weighting column should be a positive real number. If weight values are not >0, then that should throw an error. A weighting column is useful for several cases - like when the class labels are very skewed, or when you just want some records to count more heavily than others. For example, you might want a dataset of cities to be weighted by population, or a dataset of products to be weighted by price.

> Class and instance weighting for ML
> -----------------------------------
>
>                 Key: SPARK-9610
>                 URL: https://issues.apache.org/jira/browse/SPARK-9610
>             Project: Spark
>          Issue Type: Umbrella
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Priority: Major
>
> This umbrella is for tracking tasks for adding support for label or instance weights to ML algorithms.  These additions will help handle skewed or imbalanced data, ensemble methods, etc.



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