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Distinct Clustering techniques make unique assumptions on the structure of the data, often outlined by some similarity metric and evaluated, for example, by internal compactness, or even the similarity amongst members of exactly the same cluster, and separation, the distinction between clusters. Other strategies are according to believed density and https://mahavet.org/2026/01/the-smart-trick-of-learn-python-pdf-that-nobody-is-discussing/
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