A comparison of event models for naive bayes text classification

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Summary

It is found that the multi-variate Bernoulli performs well with small vocabulary sizes, but that the multinomial performs usually performs even better at larger vocabulary sizes--providing on average a 27% reduction in error over the multi -variateBernoulli model at any vocabulary size.

Type
article
Published
1998-01-01
Cited by
4,430
References
37

Keywords

Computer science, Artificial intelligence, Naive Bayes classifier, Perplexity, Vocabulary

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