Interpretable machine-learning diagnosis of forest gross primary productivity patterns in China’s protected areas
收藏Figshare2025-12-16 更新2026-04-08 收录
下载链接：
https://figshare.com/articles/dataset/Leveraging_explainable_causal_artificial_intelligence_to_study_forest_gross_primary_productivity_dynamics_in_China_s_protected_areas/29290427/2
下载链接
链接失效反馈官方服务：
资源简介：
A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.All code was written by Chenxi Zhu except the causality analysis which was written by Emmanuel Yeboah.
提供机构：
Cabral, Pedro
创建时间：
2025-12-16
