Core ML Concepts · beginner · concept 19 of 176
Naive Bayes
A classifier that applies Bayes' theorem with one bold simplification: treat every feature as independent. Wrong assumption, great results, especially on text, where it filtered spam for a decade and still makes a hard-to-beat baseline. Also the cleanest example of a generative classifier next to logistic regression's discriminative approach.
Key terms
Conditional independencePrior & likelihoodGenerative vs discriminativeSpam filteringLaplace smoothing
Learn these first
Where you meet it in the real world
Spam and abuse filters, quick text classification baselines, medical triage scoring
Videos
▶ Bayes theorem, the geometry of changing beliefs ↗
3Blue1Brown · YouTube
▶ Naive Bayes, Clearly Explained!!! ↗
StatQuest with Josh Starmer · YouTube
Guides and articles
Courses, papers, and more