So sánh phương pháp

	Thông tin tương hỗ chuẩn hóa	V-measure
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM
Năm ra đời	2005	2007
Người khởi xướng	Danon, Diaz-Guilera, Duch, Arenas	Andrew Rosenberg, Julia Hirschberg
Loại	Information-theoretic metric	Entropy-based metric
Công trình gốc	Danon, L., Diaz-Guilera, A., Duch, J., & Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, 2005(09), P09008.	Rosenberg, A., & Hirschberg, J. (2007). V-measure: A conditional entropy-based external cluster evaluation measure. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (pp. 410-420).
Tên gọi khác	NMI, mutual information, information criterion	V-measure score, homogeneity completeness V-measure
Liên quan	5	5
Tóm tắt	Normalized Mutual Information (NMI), popularized by Danon et al. in 2005, is an external clustering evaluation metric based on information theory. It measures the amount of information shared between a predicted clustering and ground truth labels, normalized to a scale between 0 and 1. A value of 1 indicates perfect agreement, while 0 indicates independence.	V-measure, introduced by Rosenberg and Hirschberg in 2007, is an external clustering evaluation metric based on the harmonic mean of homogeneity and completeness. It measures whether clusters contain only points from a single true class (homogeneity) and whether all points from a true class are assigned to the same cluster (completeness). Values range from 0 to 1.