A Gaussian process regression model to predict energy contents of corn for poultry
The present study proposes a Gaussian process regression (GPR) approach to develop a model to predict true metabolizable energy corrected for nitrogen (TMEn) content of corn samples (as model output) for poultry given levels of feed chemical compositions of crude protein, ether extract, crude fiber,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-11-01
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| Series: | Poultry Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0032579120305265 |