`nltk.PositiveNaiveBayesClassifier`¶

class nltk.PositiveNaiveBayesClassifier(label_probdist, feature_probdist)[source]¶

Methods¶

__init__(label_probdist, feature_probdist)

param label_probdist:
	P(label), the probability distribution

classify(featureset)

classify_many(featuresets) Apply self.classify() to each element of featuresets.

labels()

most_informative_features([n]) Return a list of the ‘most informative’ features used by this classifier.

prob_classify(featureset)

prob_classify_many(featuresets) Apply self.prob_classify() to each element of featuresets.

show_most_informative_features([n])

train(positive_featuresets, ...[, ...])

param positive_featuresets:
	A list of featuresets that are known as positive