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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2017/08/02 19:20:01 UTC
[jira] [Commented] (SPARK-21306) OneVsRest Conceals Columns That
May Be Relevant To Underlying Classifier
[ https://issues.apache.org/jira/browse/SPARK-21306?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16111570#comment-16111570 ]
Hyukjin Kwon commented on SPARK-21306:
--------------------------------------
User 'facaiy' has created a pull request for this issue:
https://github.com/apache/spark/pull/18764
> OneVsRest Conceals Columns That May Be Relevant To Underlying Classifier
> ------------------------------------------------------------------------
>
> Key: SPARK-21306
> URL: https://issues.apache.org/jira/browse/SPARK-21306
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.1.1
> Reporter: Cathal Garvey
> Assignee: Yan Facai (颜发才)
> Priority: Critical
> Labels: classification, ml
> Fix For: 2.2.1, 2.3.0
>
>
> Hi folks, thanks for Spark! :)
> I've been learning to use `ml` and `mllib`, and I've encountered a block while trying to use `ml.classification.OneVsRest` with `ml.classification.LogisticRegression`. Basically, [here in the code|https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala#L320], only two columns are being extracted and fed to the underlying classifiers.. however with some configurations, more than two columns are required.
> Specifically: I want to do multiclass learning with Logistic Regression, on a very imbalanced dataset. In my dataset, I have lots of imbalances, so I was planning to use weights. I set a column, `"weight"`, as the inverse frequency of each field, and I configured my `LogisticRegression` class to use this column, then put it in a `OneVsRest` wrapper.
> However, `OneVsRest` strips all but two columns out of a dataset before training, so I get an error from within `LogisticRegression` that it can't find the `"weight"` column.
> It would be nice to have this fixed! I can see a few ways, but a very conservative fix would be to include a parameter in `OneVsRest.fit` for additional columns to `select` before passing to the underlying model.
> Thanks!
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