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From "Apache Spark (JIRA)" <>
Subject [jira] [Commented] (SPARK-21306) OneVsRest Conceals Columns That May Be Relevant To Underlying Classifier
Date Thu, 06 Jul 2017 10:00:01 GMT


Apache Spark commented on SPARK-21306:

User 'facaiy' has created a pull request for this issue:

> OneVsRest Conceals Columns That May Be Relevant To Underlying Classifier
> ------------------------------------------------------------------------
>                 Key: SPARK-21306
>                 URL:
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.1.1
>            Reporter: Cathal Garvey
>            Priority: Minor
>              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|],
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 `` for additional columns to `select` before
passing to the underlying model.
> Thanks!

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