Classical models built from the math you already know
Bayes' theorem already gave a way to flip a conditional probability around: start from a prior belief, multiply by how well the evidence fits, then normalize so everything adds to one. Naive Bayes turns that single tool into a working classifier, with one bold shortcut bolted on: pretend that once you know the class, every feature is independent of every other feature.
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▶ Naive Bayes: A Probability-First Classifier