Hi there.. I'm not sure if you have been answered yet.. so perhaps I can
help
MultinomialNB has a parameter called `class_weight` which you can set at
initialization.
| class_weight : array-like, size=[n_classes,]
| Prior probabilities of the classes. If specified the priors are not
|
... or more simply:
pipeline.fit(X, y, nb__sample_weight=sample_weight)
On 10 January 2013 15:20, Gilles Louppe g.lou...@gmail.com wrote:
Hi,
I don't know how it interfaces with NLTK's SklearnClassifier, but if
you can work your way using only Scikit-Learn for training, then can
you pass
Hi all,
I found this piece of code (from
herehttp://stackoverflow.com/questions/10098533/implementing-bag-of-words-naive-bayes-classifier-in-nltk),
which basically tries to classify movie reviews into positive and negative.
Now I need to put in weights for positive and negative reviews (for
