jaccard

Comparing every pair of a million documents is a trillion comparisons. MinHash estimates Jaccard similarity from a tiny signature, and LSH turns dedup into a near-linear scan. Here is the implementation.

Pick the wrong distance metric and you quietly break kNN, clustering, and retrieval. The signal is knowing what each metric actually measures and matching it to the data: magnitude vs direction, sets, correlated features.