Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/597#issuecomment-42125991
On this note, recall there was a change a while back to handle the case of
negative confidence levels. 0 still means "don't know" and positive values mean
"confident that the prediction should be 1". Negative values means "confident
that the prediction should be 0".
I have in this case used some kind of weighted RMSE. The weight is the
absolute value of the confidence. The error is the difference between
prediction and either 1 or 0, depending on whether r is positive or negative.
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