2012/5/16 Andreas Mueller <[email protected]>:
> As far as I can see, the OneVsRestClassifier
> decides whether to do multi-class or multi-label by
> looking a the training set. This is exactly what you observe:
> If you only have on label per datapoint in the training set,
> you will only get one label back.
Yep. It looks at the labels; if a list of lists is passed in, it does
multilabel classification, e.g.
y = [["ham", "eggs"], ["spam"]]
means sample 0 has the labels "ham" and "eggs" while sample 1 has only
the label "spam".
> Looking at the OneVsRestClassifier code,
> I'm not sure where this happens. Maybe someone
> who is more familiar with this estimator can comment.
This happens in the LabelBinarizer.
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
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