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Posted to issues@spark.apache.org by "yuhao yang (JIRA)" <ji...@apache.org> on 2017/06/14 03:31:00 UTC

[jira] [Resolved] (SPARK-20348) Support squared hinge loss (L2 loss) for LinearSVC

     [ https://issues.apache.org/jira/browse/SPARK-20348?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

yuhao yang resolved SPARK-20348.
--------------------------------
    Resolution: Duplicate

Combine it with SPARK-20602 and resolve this as duplicate.

> Support squared hinge loss (L2 loss) for LinearSVC
> --------------------------------------------------
>
>                 Key: SPARK-20348
>                 URL: https://issues.apache.org/jira/browse/SPARK-20348
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>    Affects Versions: 2.2.0
>            Reporter: yuhao yang
>            Priority: Minor
>
> While Hinge loss is the standard loss function for linear SVM, Squared hinge loss (a.k.a. L2 loss) is also popular in practice. L2-SVM is differentiable and imposes a bigger (quadratic vs. linear) loss for points which violate the margin. Some introduction can be found from http://mccormickml.com/2015/01/06/what-is-an-l2-svm/
> Liblinear and [scikit learn|http://scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html] both offer squared hinge loss as the default loss function for linear SVM. 



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