Genomic selection in pig breeding: comparative analysis of machine learning algorithms.
Journal:
Genetics, selection, evolution : GSE
PMID:
40065232
Abstract
BACKGROUND: The effectiveness of genomic prediction (GP) significantly influences breeding progress, and employing SNP markers to predict phenotypic values is a pivotal aspect of pig breeding. Machine learning (ML) methods are usually used to predict phenotypic values since their advantages in processing high dimensional data. While, the existing researches have not indicated which ML methods are suitable for most pig genomic prediction. Therefore, it is necessary to select appropriate methods from a large number of ML methods as long as genomic prediction is performed. This paper compared the performance of popular ML methods in predicting pig phenotypes and then found out suitable methods for most traits.