62. Naive Bayes: Fast, Simple, Surprisingly Effective

Short summary

Naive Bayes powers spam filters and other fast classifiers by calculating conditional probabilities and treating features as independent, even though that assumption is usually false. Explains why this counterintuitive approach works, covers three variants (Gaussian, Multinomial, Bernoulli), and provides complete working code for building a text-based spam classifier with scikit-learn.

• •Naive Bayes achieves text classification in one pass by multiplying feature probabilities
• •The independence assumption is wrong but works anyway; relative class probabilities are preserved
• •Three variants exist (Gaussian for continuous data, Multinomial and Bernoulli for text); includes full scikit-learn examples

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