AI engineering glossary · Classical ML algorithms
What is Naive Bayes?
Naive Bayes: A probabilistic classifier that applies Bayes' rule and assumes features are independent of each other once the class is known. That simplification makes training a matter of counting, so it is very fast, works with little data and is a classic baseline for text classification.
Naive Bayes: an example
Classifying an SMS as spam by multiplying the class prior by the probability of each word given spam and given not-spam, then picking the larger.
Related terms
More Classical ML algorithms terms
- Non-negative matrix factorisation
- Normal equation
- Odds ratio
- One-class SVM
- One-vs-one
- One-vs-rest
- Ordinary least squares
- Out-of-bag error
Where you learn it
Naive Bayes is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.