On Sat, Aug 30, 2014 at 03:53:24PM -0400, Sebastian Raschka wrote:
> I was wondering if it somehow possible to define a loss function to the Naive 
> Bayes classifier in scikit-learn.

No.

> For example, let's assume that we are interested in spam vs. ham
> classification. In this context, such a loss function would be useful
> to lower the False Positive rate (i.e., classifying ham as spam, which
> is "worse" than classifying spam as ham)

You can shift the ratio of errors in one class vs the other by accessing
directly the output of 'predict_proba' and thresholding at a different
value than equal probability for each class.

HTH,

Gael

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