手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| 慣性× | デイビス・ボールディン指数× | |
|---|---|---|
| 分野 | モデル評価 | モデル評価 |
| 系統 | MCDM | MCDM |
| 提唱年≠ | 1967 | 1979 |
| 提唱者≠ | Stuart Lloyd, James MacQueen | David L. Davies, Donald W. Bouldin |
| 種類≠ | Clustering quality metric | Cluster quality metric |
| 原典≠ | Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. DOI ↗ | Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2), 224-227. DOI ↗ |
| 別名≠ | WCSS, within-cluster sum of squares, cluster cohesion | DBI, Davies Bouldin index |
| 関連 | 5 | 5 |
| 概要≠ | Inertia, also called Within-Cluster Sum of Squares (WCSS), is a measure of cluster cohesion that quantifies how tightly points are grouped around their cluster centroids. Lower values indicate more compact, cohesive clusters. Inertia is the primary objective function for k-means clustering and has been a fundamental metric since the method's introduction. | 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. |
| ScholarGateデータセット ↗ |
|
|