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kvorion/naivebayes-classify.py

Created December 7, 2010 05:16
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classify method
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naivebayes-classify.py
def Classify(self, featureVector): #featureVector is a simple list like the ones that we use to train
probabilityPerLabel = {} #store the final probability for each class label
for label in self.labelCounts:
logProb = 0
for featureValue in featureVector:
logProb += math.log(self.featureCounts[(label, self.featureNameList[featureVector.index(featureValue)], featureValue)]/self.labelCounts[label])
probabilityPerLabel[label] = (self.labelCounts[label]/sum(self.labelCounts.values())) * math.exp(logProb)
print probabilityPerLabel
return max(probabilityPerLabel, key = lambda classLabel: probabilityPerLabel[classLabel])
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