Naive Bayes treats features. Those features can be anything. It is, as you say, common for them to be single words, but there is no reason not to use additional features and some promise of better performance. Overtraining may be worse with more features, but with naive Bayes you are in a state of sin on that count from the start.
On Tue, Jan 26, 2010 at 3:05 AM, Loek Cleophas <[email protected]>wrote: > My understanding of 'traditional' naive Bayes is that it only considers > probabilities related to single words/tokens, independent of context. -- Ted Dunning, CTO DeepDyve
