Hi,
When going through the MLlib doc for classification:
http://spark.apache.org/docs/latest/mllib-linear-methods.html, I find that
the loss functions are based on label {1, -1}.
But in MLlib, the loss functions on label {1, 0} are used. And there is a
dataValidation check before fitting, if a label is other than 0 or 1, an
exception will be thrown.
I don't understand the intention here. Could someone explain this ?
Hao.
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