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https://issues.apache.org/jira/browse/SPARK-21306?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yanbo Liang updated SPARK-21306:
--------------------------------
Shepherd: Yanbo Liang
Target Version/s: 2.3.0
> 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
>
> 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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