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| 正規化相互情報量（Normalized Mutual Information, NMI）× | フォウルクス・マローズ指数× | |
|---|---|---|
| 分野 | モデル評価 | モデル評価 |
| 系統 | MCDM | MCDM |
| 提唱年≠ | 2005 | 1983 |
| 提唱者≠ | Danon, Diaz-Guilera, Duch, Arenas | E. B. Fowlkes, C. L. Mallows |
| 種類≠ | Information-theoretic metric | Pair-counting metric |
| 原典≠ | Danon, L., Diaz-Guilera, A., Duch, J., & Arenas, A. (2005). Comparing community structure identification. Journal of Statistical Mechanics: Theory and Experiment, 2005(09), P09008. DOI ↗ | Fowlkes, E. B., & Mallows, C. L. (1983). A method for comparing two hierarchical clusterings. Journal of the American Statistical Association, 78(383), 553-569. DOI ↗ |
| 別名≠ | NMI, mutual information, information criterion | Fowlkes Mallows, FM index |
| 関連 | 5 | 5 |
| 概要≠ | 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. | 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. |
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