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A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

Montesinos-Lopez, O.A.; Martin-Vallejo, J.; Crossa, J.; Gianola, D.; Hernández Suárez, C.M.; Montesinos-Lopez, A.; Juliana, P.; Singh, R.P. (Genetics Society of America, 2019)

Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...

Article

Maximum a posteriori Threshold Genomic Prediction model for ordinal traits

Montesinos-López, A.; Gutierrez-Pulido, H.; Montesinos-Lopez, O.A.; Crossa, J. (Genetics Society of America, 2020)

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A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

Maximum a posteriori Threshold Genomic Prediction model for ordinal traits

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A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding

Maximum a posteriori Threshold Genomic Prediction model for ordinal traits