I would think that Logistic Regression[1] could apply here.. You can feed
it binary labels and then it will act as a classifier that will return for
each label the conditional class probability values .
See [2] for scikit-learns implementation
[1] http://en.wikipedia.org/wiki/Logistic_regression
[2]
http://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
Hope it helps :)
2013/7/1 Gene Kogan <[email protected]>
> I have a regression task where I have to assign a continous label between
> 0 and 1, but my training set contains only binary labels, 0s and 1s.
> Should I treat this as a classification problem and map the labels to a
> continous line via some confidence metric (if it's available) or is there a
> regression algorithm which can be trained on binary labels? What
> scikits-learn methods will help me achieve this? Thanks!
>
> best,
> gene
>
>
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