Safari Books Online is a digital library providing on-demand subscription access to thousands of learning resources.
Bayesian classifiers were covered in Chapter 6. In that chapter, you saw how to create a document classification system, such as those used for spam filtering or dividing up a set of documents based on an ambiguous keyword search.
Although all the examples dealt with documents, the Bayesian classifier described in Chapter 6 will work on any dataset that can be turned into lists of features. A feature is simply something that is either present or absent for a given item. In the case of documents, the features are the words in the document, but they could also be characteristics of an unidentified object, symptoms of a disease, or anything else that can be said to be present of absent.