Interpretable machine-learning diagnosis of forest gross primary productivity patterns in China’s protected areas

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.