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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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