[
https://issues.apache.org/jira/browse/SPARK-2341?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14051151#comment-14051151
]
Xiangrui Meng commented on SPARK-2341:
--------------------------------------
[~srowen] Instead of taking string labels directly, we can provide tools to
convert them to integer labels (still Double typed). LIBLINEAR/LIBSVM do not
support string labels either, but they are still among the top choices for
logistic regression and SVM.
[~eustache] Unfortunately, the argument name in Scala is part of the API and
loadLibSVMFile is not marked as experimental. So we cannot update the argument
name to `multiclassOrRegression`, which is too long anyway. Could you update
the doc and change the first sentence from "multiclass: whether the input
labels contain more than two classes" to "multiclass: whether the input labels
are continuous-valued (for regression) or contain more than two classes"?
> 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
--
This message was sent by Atlassian JIRA
(v6.2#6252)
