Confidence intervals for the risks of regression models
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.
- Publisher
- SPRINGER-VERLAG BERLIN
- Issue Date
- 2006-10
- Language
- English
- Article Type
- Article; Proceedings Paper
- Citation
NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS Book Series: Lecture Notes in Computer Science, v.4232, pp.755 - 764
- ISSN
- 0302-9743
- Appears in Collection
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