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Table 4 Correlation coefficients (± standard errors) in the Jersey testing data set, by trait.1

From: Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat

  Pedigree relationships Genomic relationships
Network Fat yield Milk yield Protein yield Fat yield Milk yield Protein yield
Linear 0.11 ± 0.04 0.07 ± 0.03 0.02 ± 0.02 0.43 ± 0.02 0.42 ± 0.03 0.44 ± 0.02
1 neuron 0.23 ± 0.03 0.10 ± 0.03 0.09 ± 0.02 0.51 ± 0.02 0.45 ± 0.02 0.44 ± 0.02
2 neurons 0.22 ± 0.03 0.08 ± 0.01 0.08 ± 0.03 0.49 ± 0.02 0.46 ± 0.03 0.51 ± 0.02
3 neurons 0.22 ± 0.02 0.13 ± 0.02 0.10 ± 0.03 0.53 ± 0.02 0.52 ± 0.02 0.47 ± 0.02
4 neurons 0.20 ± 0.02 0.09 ± 0.02 0.14 ± 0.02 0.45 ± 0.03 0.52 ± 0.02 0.47 ± 0.03
5 neurons 0.23 ± 0.02 0.13 ± 0.02 0.15 ± 0.02 0.42 ± 0.03 0.50 ± 0.02 0.47 ± 0.02
6 neurons 0.27 ± 0.02 0.10 ± 0.03 0.11 ± 0.02 0.48 ± 0.04 0.54 ± 0.02 0.50 ± 0.03
  1. 1Results are the average of 20 runs based on random partitions on the data