A Stacking Ensemble Learning Framework for Genomic Prediction

Machine learning (ML) is perhaps the most useful tool for the interpretation of large genomic datasets. However, the performance of a single machine learning method in genomic selection (GS) is currently unsatisfactory. To improve the genomic predictions, we constructed a stacking ensemble learning...

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Bibliographic Details

Published in:	Frontiers in Genetics
Main Authors:	Mang Liang, Tianpeng Chang, Bingxing An, Xinghai Duan, Lili Du, Xiaoqiao Wang, Jian Miao, Lingyang Xu, Xue Gao, Lupei Zhang, Junya Li, Huijiang Gao
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2021-03-01
Subjects:	ensemble learning stacking genomic prediction machine learning prediction accuracy
Online Access:	https://www.frontiersin.org/articles/10.3389/fgene.2021.600040/full