ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP

ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP

Machine learning has attracted much attention in the field of genomic prediction due to its powerful predictive capabilities, yet the lack of an explanatory nature in modeling decisions remains a major challenge. In this study, we propose a novel machine learning method, ExAutoGP, which aims to impr...

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Bibliographic Details
Main Authors: Yao Rao, Lilian Zhang, Lutao Gao, Shuran Wang, Linnan Yang
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Animals
Subjects:
genomic selection
genomic prediction
automated machine learning
SHapley additive exPlanations
animal breeding
ExAutoGP
Online Access:https://www.mdpi.com/2076-2615/15/8/1172
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