AI engineering glossary · Classical ML algorithms
What is Multinomial naive Bayes?
Multinomial naive Bayes: A naive Bayes version for count data, such as how often each word appears in a document. It models word counts per class as a multinomial distribution and is a long-standing text classification baseline.
Multinomial naive Bayes: an example
Classifying news articles as sports or politics from word counts, where 'wicket' appears 5 times in one article.
Related terms
More Classical ML algorithms terms
- Multiple linear regression
- Naive Bayes
- Non-negative matrix factorisation
- Normal equation
- Odds ratio
- One-class SVM
- One-vs-one
- One-vs-rest
Where you learn it
Multinomial 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.