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XGBoost is the optimization of gradient boosting with the best overall performance among machine learning algorithms. By introducing a regularization term into the loss function of gradient boosting, XGBoost can effectively limit the complexity of the model, improve the generalization ability, and solve the overfitting problem. In this paper, XGBoost is first introduced into modeling radio‐frequency...
Autumn phenology plays a critical role in regulating growing season length and matter and energy exchanges in terrestrial ecosystems. The climate‐driven mechanism of the grassland autumn phenology process and its spatial distribution patterns at the hemispheric scale are, however, still poorly understood. In this study, we employed 17 existing and modified models to simulate the satellite‐derived...