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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