What are different types of Naïve Bayes classifiers?

Updated May 17, 2026

Short answer

Common types include Gaussian, Multinomial, and Bernoulli Naïve Bayes.

Deep explanation

Gaussian NB is used for continuous data, Multinomial NB for count-based data (like text frequency), and Bernoulli NB for binary features. Each variant adapts likelihood estimation to different data distributions.

Real-world example

Spam filtering uses Multinomial NB on word counts.

Common mistakes

  • Using Gaussian NB on sparse text data.

Follow-up questions

  • When should you use Bernoulli NB?
  • What is Gaussian assumption?

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