Journal article
Bayesian wavelet networks for nonparametric regression.
- Abstract:
-
Radial wavelet networks have recently been proposed as a method for nonparametric regression. In this paper we analyze their performance within a Bayesian framework. We derive probability distributions over both the dimension of the networks and the network coefficients by placing a prior on the degrees of freedom of the model. This process bypasses the need to test or select a finite number of networks during the modeling process. Predictions are formed by mixing over many models of varying ...
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- Publication status:
- Published
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- Publisher copy:
- 10.1109/72.822507
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Authors
Bibliographic Details
- Publisher:
- IEEE
- Journal:
- IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council
- Volume:
- 11
- Issue:
- 1
- Pages:
- 27-35
- Publication date:
- 2000-01-01
- DOI:
- EISSN:
-
1941-0093
- ISSN:
-
1045-9227
- Source identifiers:
-
104743
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:104743
- UUID:
-
uuid:393c7bfc-5e5f-4b1d-a933-6cdb13fd4ce3
- Local pid:
- pubs:104743
- Deposit date:
- 2012-12-19
Terms of use
- Copyright date:
- 2000
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