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Boston University

A naïve Bayes classifier using only individual word features of all of the words in a given text is similar to language modeling. Such a naïve Bayes model can be viewed as a set of class-specific unigram language models, in which the model for each class instantiates a unigram language model.

The model also assigns a probability to each sentence:

$ P(s|c) = \sum_{i\in positions}P(w_i|c) $

Naïve Bayes as a Language Model

An on-going but a helpful book resource about NLP
https://web.stanford.edu/~jurafsky/slp3/

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