方法对比

	福尔克斯-马洛斯指数	V-measure
领域	模型评估	模型评估
方法族	MCDM	MCDM
起源年份	1983	2007
提出者	E. B. Fowlkes, C. L. Mallows	Andrew Rosenberg, Julia Hirschberg
类型	Pair-counting metric	Entropy-based metric
开创性文献	Fowlkes, E. B., & Mallows, C. L. (1983). A method for comparing two hierarchical clusterings. Journal of the American Statistical Association, 78(383), 553-569.	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).
别名	Fowlkes Mallows, FM index	V-measure score, homogeneity completeness V-measure
相关	5	5
摘要	The Fowlkes-Mallows Index, introduced by Fowlkes and Mallows in 1983, is an external clustering evaluation metric based on the geometric mean of precision and recall. It measures agreement between two partitions by examining pairs of points and how they are grouped in both the predicted and ground truth clusterings. Values range from 0 to 1, with 1 indicating perfect agreement.	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.