A Short Intro to Naive Bayesian Classifiers

This document introduces Naive Bayes classifiers and their use in document classification. It begins with an overview of Naive Bayes theory and classifiers. Examples are then provided to illustrate how to estimate probabilities for the classifier from sample training data and how to perform classification of new documents. The assumptions and advantages of the Naive Bayes approach are discussed. In particular, it notes that Naive Bayes classifiers can be efficiently constructed, even with many attributes, and generally perform well despite their "naivety".