Naive Bayes
← Back to Classical ML Algorithms
Probabilistic classifier based on Bayes’ theorem with a strong (naive) independence assumption between features. Surprisingly effective for text classification despite the assumption rarely holding.
Key Properties
- Bayes’ theorem: P(y|x) = P(x|y) * P(y) / P(x)
- Feature independence assumption
- Variants: Gaussian, Multinomial, Bernoulli
Related
- Bayesian Methods (broader Bayesian approach)
- Text Features (Naive Bayes excels at text)