Naive Bayes Classifier

The basic asumption when using a Naive Bayes classifier is that each feature pair being classified is independant of each other and contributes equally to the outcome.

Naive Bayes classifiers have worked quite well in many real-world situations, e.g. document classification and spam filtering. 

They require a small amount of training data to estimate the necessary parameters.

Naive Bayes learners and classifiers can be extremely fast compared to more sophisticated methods.