added PositiveNaiveBayesClassifier
Merge branch 'master' of git://github.com/nltk/nltk into positive-naivebayes
Added docstrings
Added import from nltk.classify
Better documented the demo
Train returns a PositiveNaiveBayesClassifier, not a NBC
Reverting to plain defaultdict(FreqDist) as in NaiveBayesClassifier
Normalize probdist of P(fname=fval|0, fname), since we are setting negative values to zero
Added a TODO note for smoothing the P(feature|0) distribution.
Added doctest and a few comments
Removed trailing newlines
nltk.Tree -> Tree
another nltk.Tree -> Tree
Merge pull request #230 from japerk/patch-1

nltk.Tree -> Tree
Merge pull request #225 from apresta/positive-naivebayes

Positive Naive Bayes Classifier
Exclude common 'nltk.' prefix from module index.
Merge pull request #231 from pjdelport/master

Exclude common 'nltk.' prefix from module index.
this file correspond to the generalized hamming distance
it can be used as a metric for text segmentation
it can be used the same way as the windowdiff metric, and has the same role

this implementation is a python translation of V. Kulyukin C++ code
(co-author of the paper on generalized hamming distance)
the examples in the demo function are the same that were used in
Kulyukin implementation, and allowed to compare the good behavior
of this metric to Kulyukin implementation, considered as a reference
same tests in demo, but output now more human-friendly
minor coding style changes
Beeferman's pk measure