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https://issues.apache.org/jira/browse/SPARK-3246?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15783435#comment-15783435
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Sheridan Rawlins commented on SPARK-3246:
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Hey, I have a solution that just uses liblinear to do the work. Not sure if
that would be acceptable to commit the added dependencies, but if it is, I also
did the spark.ml port to gain all of the cross validation / hypertuning goodness
-SCR
Sent from my iPhone
> Support weighted SVMWithSGD for classification of unbalanced dataset
> --------------------------------------------------------------------
>
> Key: SPARK-3246
> URL: https://issues.apache.org/jira/browse/SPARK-3246
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 0.9.0, 1.0.2
> Reporter: mahesh bhole
>
> Please support weighted SVMWithSGD for binary classification of unbalanced
> dataset.Though other options like undersampling or oversampling can be
> used,It will be good if we can have a way to assign weights to minority
> class.
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