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https://issues.apache.org/jira/browse/SPARK-2341?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14078040#comment-14078040
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Sean Owen commented on SPARK-2341:
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To me, it's less confusing than writing "multiclass" for a regression problem.
Yes I also think it could be simpler to remove multiclass; the idea I suppose
is that binary is merely a special case of that, and the caller can write the
required transformation to 0/1 if needed. At least the caller is aware of the
transformation and I think that's good. At least, there you just let numbers be
numbers and let downstream code figure out whether the number is a continuous
value, or the number is a category.
> loadLibSVMFile doesn't handle regression datasets
> -------------------------------------------------
>
> Key: SPARK-2341
> URL: https://issues.apache.org/jira/browse/SPARK-2341
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.0.0
> Reporter: Eustache
> Priority: Minor
> Labels: easyfix
>
> Many datasets exist in LibSVM format for regression tasks [1] but currently
> the loadLibSVMFile primitive doesn't handle regression datasets.
> More precisely, the LabelParser is either a MulticlassLabelParser or a
> BinaryLabelParser. What happens then is that the file is loaded but in
> multiclass mode : each target value is interpreted as a class name !
> The fix would be to write a RegressionLabelParser which converts target
> values to Double and plug it into the loadLibSVMFile routine.
> [1] http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html
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