How would you mentally reconstruct KNN from scratch during an interview?

You define similarity, compute distances, select neighbors, and aggregate outcomes.

Start from first principles: assume similar points behave similarly. Define a distance metric, compute distances from query to dataset, select K closest points, and aggregate their labels. This reconstruction shows deep understanding beyond memorization.