|
| << vorige |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 12 van 12 gevonden artikelen
| Titel: |
Visualizable and interpretable regression models with good prediction power |
| Auteur: |
Kim, Hyunjoong Loh, Wei-Yin Shih, Yu-Shan Chaudhuri, Probal |
| Verschenen in: |
IIE transactions |
| Paginering: | Jaargang 39 (2007) nr. 6 pagina's 565-579 |
| Jaar: |
2007-06 |
| Inhoud: |
Many methods can fit models with a higher prediction accuracy, on average, than the least squares linear regression technique. But the models, including linear regression, are typically impossible to interpret or visualize. We describe a tree-structured method that fits a simple but nontrivial model to each partition of the variable space. This ensures that each piece of the fitted regression function can be visualized with a graph or a contour plot. For maximum interpretability, our models are constructed with negligible variable selection bias and the tree structures are much more compact than piecewise-constant regression trees. We demonstrate, by means of a large empirical study involving 27 methods, that the average prediction accuracy of our models is almost as high as that of the most accurate “black-box” methods from the statistics and machine learning literature. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 12 van 12 gevonden artikelen
| << vorige |