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Sheridan Rawlins commented on SPARK-3246: ----------------------------------------- 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org