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When k-means Clustering Fails

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Letting the computer automatically find groupings in data is incredibly powerful and is at the heart of “data mining” and “machine learning”. One of the most widely used methods for clustering data is k-means clustering. Unfortunately, k-means clustering can fail spectacularly as in the example below. Centroid-based clustering algorithms work on multi-dimensional data by partitioning data points into k clusters such that…
Original Post: When k-means Clustering Fails

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