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。
| 精度× | 平均絶対誤差 (MAE)× | |
|---|---|---|
| 分野 | モデル評価 | モデル評価 |
| 系統 | MCDM | MCDM |
| 提唱年≠ | 20th century | 1799 |
| 提唱者≠ | Historical statistical foundations | Pierre-Simon Laplace |
| 種類≠ | Evaluation metric | Robust distance-based metric |
| 原典≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat. link ↗ |
| 別名≠ | Overall Accuracy, Correct Classification Rate | MAE, L1 error, mean absolute deviation |
| 関連≠ | 5 | 3 |
| 概要≠ | Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class. | Mean Absolute Error is a robust metric that measures the average absolute magnitude of prediction errors in regression models. Dating back to Pierre-Simon Laplace's work on observational errors (1799), MAE quantifies typical prediction deviation by averaging the absolute differences between observed and predicted values. |
| ScholarGateデータセット ↗ |
|
|