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

BMC Genomic Data

Table 3 Prediction mean squared errors (± standard errors) by trait: Jerseys.¹

Network	Fat yield (pedigree)	Fat yield (genomic)	Milk yield (pedigree)	Milk yield (genomic)	Protein yield (pedigree)	Protein yield (genomic)
Linear	1.19 ± 0.07	0.86 ± 0.05	1.09 ± 0.05	0.88 ± 0.04	1.00 ± 0.04	0.75 ± 0.07
1 neuron	1.01 ± 0.04	0.74 ± 0.03	0.99 ± 0.04	0.81 ± 0.03	0.97 ± 0.04	0.71 ± 0.04
2 neurons	0.93 ± 0.05	0.70 ± 0.03	0.96 ± 0.05	0.76 ± 0.04	1.02 ± 0.04	0.72 ± 0.04
3 neurons	0.92 ± 0.04	0.71 ± 0.03	0.98 ± 0.02	0.78 ± 0.04	0.96 ± 0.06	0.80 ± 0.04
4 neurons	0.99 ± 0.04	0.84 ± 0.04	0.98 ± 0.04	0.72 ± 0.04	0.90 ± 0.06	0.70 ± 0.03
5 neurons	0.99 ± 0.04	0.86 ± 0.04	1.00 ± 0.05	0.80 ± 0.04	0.93 ± 0.04	0.77 ± 0.04
6 neurons	0.95 ± 0.03	0.77 ± 0.04	1.02 ± 0.05	0.79 ± 0.03	0.95 ± 0.03	0.76 ± 0.05

ISSN: 2730-6844