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Two fixes in NaiveBayesClassifier #224

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merged 1 commit into from Feb 18, 2012
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Two fixes in NaiveBayesClassifier #224

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6 changes: 3 additions & 3 deletions nltk/classify/naivebayes.py
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Expand Up @@ -34,7 +34,7 @@


from collections import defaultdict from collections import defaultdict


from nltk.probability import FreqDist, DictionaryProbDist, ELEProbDist, sum_logs from nltk.probability import FreqDist, ConditionalFreqDist, DictionaryProbDist, ELEProbDist, sum_logs


from api import ClassifierI from api import ClassifierI


Expand Down Expand Up @@ -94,7 +94,7 @@ def prob_classify(self, featureset):
# Otherwise, we'll just assign a probability of 0 to # Otherwise, we'll just assign a probability of 0 to
# everything. # everything.
featureset = featureset.copy() featureset = featureset.copy()
for fname in featureset: for fname in featureset.keys():
for label in self._labels: for label in self._labels:
if (label, fname) in self._feature_probdist: if (label, fname) in self._feature_probdist:
break break
Expand Down Expand Up @@ -184,7 +184,7 @@ def train(labeled_featuresets, estimator=ELEProbDist):
i.e., a list of tuples ``(featureset, label)``. i.e., a list of tuples ``(featureset, label)``.
""" """
label_freqdist = FreqDist() label_freqdist = FreqDist()
feature_freqdist = defaultdict(FreqDist) feature_freqdist = ConditionalFreqDist()
feature_values = defaultdict(set) feature_values = defaultdict(set)
fnames = set() fnames = set()


Expand Down