the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparative analysis of serum anti-Müllerian hormone (AMH) levels in sheep: the role of genetic background and physiological status
Davut Koca
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This study demonstrates the applicability of an explainable machine learning framework (XGBoost + SHAP) for investigating reproductive performance in dairy cows. Although the predictive performance of the independent test dataset was limited (R² = 0.01), SHAP provided transparent global- and individual-level explanations of model predictions, highlighting the methodological potential of explainable artificial intelligence for veterinary data analysis.
This study demonstrates the applicability of an explainable machine learning framework (XGBoost + SHAP) for investigating reproductive performance in dairy cows. Although the predictive performance of the independent test dataset was limited (R² = 0.01), SHAP provided transparent global- and individual-level explanations of model predictions, highlighting the methodological potential of explainable artificial intelligence for veterinary data analysis.