nltk.classify.api.MultiClassifierI

class documentation

class MultiClassifierI(object): (source)

View In Hierarchy

A processing interface for labeling tokens with zero or more category labels (or "labels"). Labels are typically strs or ints, but can be any immutable type. The set of labels that the multi-classifier chooses from must be fixed and finite.

Subclasses must define:
  • labels()
  • either classify() or classify_many() (or both)
Subclasses may define:
  • either prob_classify() or prob_classify_many() (or both)
Method classify No summary
Method classify_many Apply self.classify() to each element of featuresets. I.e.:
Method labels No summary
Method prob_classify No summary
Method prob_classify_many Apply self.prob_classify() to each element of featuresets. I.e.:
def classify(self, featureset): (source)
Returns
set(label)the most appropriate set of labels for the given featureset.
def classify_many(self, featuresets): (source)

Apply self.classify() to each element of featuresets. I.e.:

return [self.classify(fs) for fs in featuresets]
Returns
list(set(label))Undocumented
def labels(self): (source)
Returns
list of (immutable)the list of category labels used by this classifier.
def prob_classify(self, featureset): (source)
Returns
ProbDistIa probability distribution over sets of labels for the given featureset.
def prob_classify_many(self, featuresets): (source)

Apply self.prob_classify() to each element of featuresets. I.e.:

return [self.prob_classify(fs) for fs in featuresets]
Returns
list(ProbDistI)Undocumented