Machine learningMachine learning

Online Naive Bayes

Online Naive Bayes is an incremental adaptation of the classical Naive Bayes classifier that updates its class-conditional statistics one observation (or one mini-batch) at a time, making it well suited to data streams, very large datasets that cannot be held in memory, and settings where the model must adapt continuously as new labeled examples arrive.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Domingos, P. & Hulten, G. (2000). Mining high-speed data streams. Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 71–80. ACM. DOI: 10.1145/347090.347107
  2. Online machine learning. Wikipedia. link

Related methods

Referenced by

ScholarGateOnline Naive Bayes (Online (Incremental) Naive Bayes Classifier). Retrieved 2026-06-04 from https://scholargate.app/en/machine-learning/online-naive-bayes