Hi everybody.
I just stumbled across an issue that comes up in the OutputCode classifier.
It may happen that a dataset is passed through that only has one class.
This leads to numeric issues in naive Bayes down the road.

I feel that if a classifier is given only one class, it should somehow 
complain
and not try to train.
What do you think about that? Should all classifiers check their input 
in this way?
Or do we just try to fit the classifier any way?

Cheers,
Andy

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