GitHub user hhbyyh opened a pull request:
https://github.com/apache/spark/pull/17645
[SPARK-20348] [ML] Support squared hinge loss (L2 loss) for LinearSVC
## What changes were proposed in this pull request?
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 both offer squared hinge loss as the default
loss function for linear SVM.
## How was this patch tested?
strengthen existing unit test and add new unit test for comparison.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/hhbyyh/spark svml2loss
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17645.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17645
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commit 6541f69401653d7e9ebfff9d573d87daba108084
Author: Yuhao Yang <[email protected]>
Date: 2017-04-16T00:38:21Z
add l2 loss
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