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