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Two Naive Bayes Models
Model 1: Multivariate Bernoulli
One feature Xw for each word in dictionary
for loop iterates over dictionary
Xw = true in document d if w appears in d
Naive Bayes assumption:
Given the document’s topic, appearance of one word in the document tells us nothing about chances that another word appears
This is the model used in the binary independence model in classic probabilistic relevance feedback on hand-classified data
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