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| Chỉ số Rand Điều chỉnh× | V-measure× | |
|---|---|---|
| Lĩnh vực | Đánh giá mô hình | Đánh giá mô hình |
| Họ | MCDM | MCDM |
| Năm ra đời≠ | 1985 | 2007 |
| Người khởi xướng≠ | Lawrence Hubert, Phipps Arabie | Andrew Rosenberg, Julia Hirschberg |
| Loại≠ | External similarity metric | Entropy-based metric |
| Công trình gốc≠ | Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1), 193-218. DOI ↗ | 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). link ↗ |
| Tên gọi khác | ARI, adjusted Rand coefficient | V-measure score, homogeneity completeness V-measure |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | The Adjusted Rand Index (ARI), developed by Hubert and Arabie in 1985, is an external clustering evaluation metric that measures the agreement between a predicted clustering and a ground truth labeling. It ranges from -1 to 1, where 1 indicates perfect agreement, 0 indicates random clustering, and negative values indicate performance worse than random chance. | 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. |
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