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How do k-NN and Naive Bayes work, and what are their assumptions and tradeoffs?

Two simple classifiers that still appear in interviews because they test whether you understand assumptions and tradeoffs, not just sklearn calls. The signal is k-NN's laziness and curse of dimensionality versus Naive Bayes' independence assumption. Here is the answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Two simple classifiers that still appear in interviews because they test whether you understand assumptions and tradeoffs, not just sklearn calls. The signal is k-NN's laziness and curse of dimensionality versus Naive Bayes' independence assumption. Here is the answer.

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