Comparing different probability models in terms of their effects on classification under a Naive Bayes assumption is likely to yield very conservative results, since the Naive Bayes classifier can perform accurate classifications under many kinds of adverse conditions and even when highly inaccurate probability estimates are used (Domingos and Pazzani, 1996;Garg and Roth, 2001).
an evaluation in terms of document classification has the advantages, compared with language modeling, of computational simplicity and the ability to benefit from information about non-occurrences of words.