So sánh phương pháp

	Chỉ số Calinski-Harabasz	Chỉ số Davies-Bouldin	Chỉ số Dunn
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM	MCDM
Năm ra đời	1974	1979	1974
Người khởi xướng	Tadeusz Calinski, Jerzy Harabasz	David L. Davies, Donald W. Bouldin	Joseph C. Dunn
Loại	Cluster quality metric	Cluster quality metric	Cluster quality metric
Công trình gốc	Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1-27.	Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2), 224-227.	Dunn, J. C. (1974). Well-separated clusters and optimal fuzzy partitions. Journal of Cybernetics, 4(1), 95-104.
Tên gọi khác	variance ratio criterion, pseudo F-statistic, CH index	DBI, Davies Bouldin index	Dunn's index, separation coefficient
Liên quan	5	5	5
Tóm tắt	The Calinski-Harabasz Index, also called the Variance Ratio Criterion, was introduced by Calinski and Harabasz in 1974. It is a metric that measures the ratio of between-cluster variance to within-cluster variance, adjusted for the number of clusters and data points. Higher values indicate better-separated, more compact clusters.	The Davies-Bouldin Index, introduced by Davies and Bouldin in 1979, is a metric for evaluating clustering quality based on the average similarity between each cluster and its most similar neighboring cluster. Lower values indicate better clustering, with a minimum of 0 representing perfectly separated, non-overlapping clusters.	The Dunn Index, introduced by Joseph C. Dunn in 1974, is a metric that captures cluster quality by measuring the ratio of the minimum between-cluster distance to the maximum within-cluster diameter. Higher values indicate well-separated and compact clusters, with better clustering quality.