An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest

Xin Xiaoa Institute of International Rivers and Eco-security, Yunnan University, Kunming, ChinaView further author information

Yi Zoua Institute of International Rivers and Eco-security, Yunnan University, Kunming, ChinaView further author information

Jiangcheng Huanga Institute of International Rivers and Eco-security, Yunnan University, Kunming, China;b Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming, ChinaView further author information

Xuan Luoa Institute of International Rivers and Eco-security, Yunnan University, Kunming, ChinaView further author information

Luyi Yanga Institute of International Rivers and Eco-security, Yunnan University, Kunming, ChinaView further author information

Meng Lic Yunnan Meteorological Bureau, Kunming, ChinaView further author information

Pengwu Yangc Yunnan Meteorological Bureau, Kunming, ChinaView further author information

Xuan Jia Institute of International Rivers and Eco-security, Yunnan University, Kunming, China;b Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming, ChinaView further author information

Yungang Lia Institute of International Rivers and Eco-security, Yunnan University, Kunming, China;b Yunnan Key Laboratory of International Rivers and Transboundary Eco-Security, Yunnan University, Kunming, ChinaCorrespondence[email protected]
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An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest

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An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest

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