What is Naive Bayes?

Naive Bayes is a probabilistic classifier based on Bayes' theorem with the "naive" assumption that features are conditionally independent given the class. Despite this unrealistic assumption, it works surprisingly well in practice, especially for text classification (spam filtering, sentiment analysis). It is extremely fast to train and predict, handles high-dimensional data well, and requires very little data. Variants include Gaussian NB (continuous features), Multinomial NB (word counts), and Bernoulli NB (binary features).