A
Bayesian filter classifies emails as spam or legitimate using statistical probability — learning from word frequency patterns in known spam vs. ham (legitimate email).
Bayesian filters improve with training — more data = better classification. Spammers use tricks to fool them: misspellings, image-based text, random word padding. Modern spam filters combine Bayesian with reputation, sender policy, and ML.