An interpretable integrated machine learning framework for genomic selection

An interpretable integrated machine learning framework for genomic selection

Although machine learning (ML) methods have shown growing promise for genomic selection (GS), several key challenges hinder their widespread application. In this study, we conducted a comprehensive analysis comparing the performance of various ML models, along with investigations into parameter opti...

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Bibliographic Details
Main Authors: Jinbu Wang, Jia Zhang, Wenjie Hao, Wencheng Zong, Mang Liang, Fuping Zhao, Longchao Zhang, Lixian Wang, Huijiang Gao, Ligang Wang
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Smart Agricultural Technology
Subjects:
Genomic selection
Pig
Machine learning
Dimensionality reduction
Interpretability
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525003703
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