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https://issues.apache.org/jira/browse/SPARK-20602?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15997314#comment-15997314
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yuhao yang commented on SPARK-20602:
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cc [~josephkb]
> Adding LBFGS as optimizer for LinearSVC
> ---------------------------------------
>
> Key: SPARK-20602
> URL: https://issues.apache.org/jira/browse/SPARK-20602
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.2.0
> Reporter: yuhao yang
>
> Currently LinearSVC in Spark only supports OWLQN as the optimizer ( check
> https://issues.apache.org/jira/browse/SPARK-14709). I made comparison between
> LBFGS and OWLQN on several public dataset and found LBFGS converges much
> faster for LinearSVC in most cases.
> The following table presents the number of training iterations and f1 score
> of both optimizers until convergence
> ||Dataset||LBFGS||OWLQN||
> |news20.binary| 31 (0.99) | 413(0.99) |
> |mushroom| 28(1.0) | 170(1.0)|
> |madelon|143(0.75) | 8129(0.70)|
> |breast-cancer-scale| 15(1.0) | 16(1.0)|
> |phishing | 329(0.94) | 231(0.94) |
> |a1a(adult) | 466 (0.87) | 282 (0.87) |
> |a7a | 237 (0.84) | 372(0.84) |
> data source:
> https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html
> training code: new LinearSVC().setMaxIter(10000).setTol(1e-6)
> LBFGS requires less iterations in most cases (except for a1a) and probably is
> a better default optimizer.
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