Article Versions Notes

Yang L, Zhou W, Zhang C, Tang F. A Comparative Machine Learning Study Identifies Light Gradient Boosting Machine (LightGBM) as the Optimal Model for Unveiling the Environmental Drivers of Yellowfin Tuna (Thunnus albacares) Distribution Using SHapley Additive exPlanations (SHAP) Analysis. Biology. 2025; 14(11):1567. https://doi.org/10.3390/biology14111567

Yang, Ling, Weifeng Zhou, Cong Zhang, and Fenghua Tang. 2025. "A Comparative Machine Learning Study Identifies Light Gradient Boosting Machine (LightGBM) as the Optimal Model for Unveiling the Environmental Drivers of Yellowfin Tuna (Thunnus albacares) Distribution Using SHapley Additive exPlanations (SHAP) Analysis" Biology 14, no. 11: 1567. https://doi.org/10.3390/biology14111567

Yang, L., Zhou, W., Zhang, C., & Tang, F. (2025). A Comparative Machine Learning Study Identifies Light Gradient Boosting Machine (LightGBM) as the Optimal Model for Unveiling the Environmental Drivers of Yellowfin Tuna (Thunnus albacares) Distribution Using SHapley Additive exPlanations (SHAP) Analysis. Biology, 14(11), 1567. https://doi.org/10.3390/biology14111567