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Why I picked the clustering model with the lower score

In my customer segmentation project, three clustering algorithms competed and the one with the best score lost. Algorithm Clusters Noise points Silhouette score K-Means 3 0 0.498 Hierarchical (Ward) 3 0 0.473 DBSCAN 2 47 0.578 If you only read the last column, DBSCAN wins. I shipped K-Means. This p…

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  1. 2026-11-13 07:25 · DEV Community — Machine Learning
    Why I picked the clustering model with the lower score

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