Hi,
A while ago, somebody asked about getting a confidence value of a
prediction with MLlib's implementation of Naive Bayes's classification.
I was wondering if there is any plan in the near future for the predict
function to return both a label and a confidence/probability? Or could the
private variables in the various machine learning models be exposed so we
could write our own functions which return both?
Having a confidence/probability could be very useful in real application.
For one thing, you can choose to trust the predicted label only if it has a
high confidence level. Also, if you want to combine the results from
multiple classifiers, the confidence/probability could be used as some kind
of weight for combining.
Thanks,
Jianguo