One cluster dominates in k-means — what do you do?

medium

Answer

$(1) Try higher k — the 'big' cluster may naturally split.$
$(2) Log-scale skewed features.$
$(3) Try k-medoids (robust to imbalanced density).$
$(4) Use HDBSCAN which handles varying densities.$
$(5) Balanced k-means variants that constrain cluster size.$
$(6) Sanity-check with silhouette per cluster — often the dominant cluster is a garbage-collector for outliers or non-standardized features.$

Check yourself — multiple choice

Cannot fix
Higher k / log-transform / k-medoids / HDBSCAN / balanced k-means; check per-cluster silhouette — big cluster often absorbs outliers
Random
Only add k

Imbalanced clusters: transform / higher k / k-medoids / HDBSCAN; check silhouette.

#clustering

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