方法对比
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| R平方 (R²)× | 调整R方 (R²_adj)× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 1896 | 1961 |
| 提出者≠ | Karl Pearson | Henri Theil |
| 类型≠ | Goodness-of-fit metric | Penalized goodness-of-fit metric |
| 开创性文献≠ | Pearson, K. (1896). Mathematical contributions to the theory of evolution. Philosophical Transactions of the Royal Society A, 187, 253-318. link ↗ | Theil, H. (1961). Economic Forecasts and Policy. Amsterdam: North-Holland Publishing Company. link ↗ |
| 别名≠ | R², coefficient of determination, r2 score | Adjusted R², R²_adj |
| 相关 | 5 | 5 |
| 摘要≠ | The coefficient of determination, denoted R², measures the proportion of variance in the dependent variable explained by the independent variables in a regression model. Introduced by Karl Pearson in the late 19th century, R² is one of the most widely used metrics for assessing how well a model fits observed data. | Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addresses the fundamental limitation of standard R²: the tendency to increase whenever any predictor is added, regardless of whether that predictor contributes meaningfully to explaining the target variable. |
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