Abstract
The empirical risks of regression models are not accurate since they are evaluated from the finite number of samples. In this context, we investigate the confidence intervals for the risks of regression models, that is, the intervals between the expected and empirical risks. The suggested method of estimating confidence intervals can provide a tool for predicting the performance of regression models. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Koo, I., & Kil, R. M. (2006). Confidence intervals for the risks of regression models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4232 LNCS, pp. 755–764). Springer Verlag. https://doi.org/10.1007/11893028_84
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
