Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Prova d'adequació× | Coeficient de determinació (R²)× | |
|---|---|---|
| Camp | Avaluació de models | Avaluació de models |
| Família | MCDM | MCDM |
| Any d'origen≠ | 1900 | 1896 |
| Autor original | Karl Pearson | Karl Pearson |
| Tipus≠ | Hypothesis testing framework for model adequacy | Goodness-of-fit metric |
| Font seminal≠ | Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157-175. DOI ↗ | Pearson, K. (1896). Mathematical contributions to the theory of evolution. Philosophical Transactions of the Royal Society A, 187, 253-318. link ↗ |
| Àlies | goodness of fit test, GOF test, model fit assessment | R², coefficient of determination, r2 score |
| Relacionats≠ | 4 | 5 |
| Resum≠ | Goodness-of-fit (GOF) testing is a framework for assessing whether observed data are consistent with a hypothesized probability distribution or model. Originating from Karl Pearson's chi-square test (1900), GOF tests quantify the discrepancy between data and model predictions, yielding p-values to judge whether observed deviations are statistically significant or due to random chance. | 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. |
| ScholarGateConjunt de dades ↗ |
|
|