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Sean Owen commented on SPARK-2341: ---------------------------------- 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 -- This message was sent by Atlassian JIRA (v6.2#6252)