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Why Perfect Clustering Algorithms Don't Exist

As software engineers, we use clustering algorithms all the time. Whether it's grouping similar users, categorizing content, or detecting patterns in data, clustering seems deceptively simple: just group similar things together, right? You might have used k-means, DBSCAN, or agglomerative clustering, thinking you just need to pick the right algorithm for your use case.But here's what most tutorials won't tell you: every clustering algorithm you choose is fundamentally flawed. Not because of poor...

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