So sánh phương pháp

	Phân cụm phân cấp mạnh mẽ	Mô hình hóa hỗn hợp
Lĩnh vực	Thống kê	Thống kê
Họ	Latent structure	Latent structure
Năm ra đời	1990	1894
Người khởi xướng	Kaufman & Rousseeuw (building on Ward, 1963 and others)	Karl Pearson
Loại	Robust unsupervised clustering	Latent variable / density estimation
Công trình gốc	Kaufman, L. & Rousseeuw, P. J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley. ISBN: 978-0471878766	McLachlan, G. J. & Peel, D. (2000). Finite Mixture Models. Wiley-Interscience. ISBN: 978-0471006268
Tên gọi khác	robust agglomerative clustering, outlier-resistant hierarchical clustering, robust linkage clustering, RHC	finite mixture model, mixture distribution model, FMM, model-based clustering
Liên quan	5	6
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.	Mixture modeling assumes that a population is composed of K unobserved subpopulations, each described by its own probability distribution. The observed data are treated as draws from a weighted combination of these component distributions. It provides a principled, model-based alternative to ad hoc clustering and supports formal comparison of solutions with different numbers of components.