So sánh phương pháp

	Phân cụm phân cấp mạnh mẽ	Phân cụm phân cấp
Lĩnh vực	Thống kê	Học máy
Họ	Latent structure	Machine learning
Năm ra đời	1990	1963
Người khởi xướng	Kaufman & Rousseeuw (building on Ward, 1963 and others)	Ward, J. H.
Loại	Robust unsupervised clustering	Unsupervised clustering (agglomerative)
Công trình gốc	Kaufman, L. & Rousseeuw, P. J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley. ISBN: 978-0471878766	Ward, J. H. (1963). Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association, 58(301), 236–244.
Tên gọi khác	robust agglomerative clustering, outlier-resistant hierarchical clustering, robust linkage clustering, RHC	Hiyerarşik Kümeleme, hiyerarşik kümeleme, agglomerative clustering, hierarchical agglomerative clustering
Liên quan	5	4
Tóm tắt	Robust hierarchical clustering extends classical agglomerative or divisive hierarchical clustering by replacing sensitive distance measures and linkage criteria with outlier-resistant alternatives, preserving cluster structure even when data contain anomalous observations or heavy-tailed distributions.	Hierarchical clustering is an unsupervised method that groups observations into nested clusters and draws the result as a dendrogram, so the number of clusters need not be fixed in advance. Its agglomerative form rests on the objective-function grouping criterion introduced by Joe Ward in 1963.