An Explainable Machine-Learning Framework Based on XGBoost–SHAP and Big Data for Revealing the Socioeconomic Drivers of Population Urbanization in China

Ziheng Shangguan

Open source

DOI
10.3390/systems13080679
Published
08
Container
Systems
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/systems13080679,
  title = {An Explainable Machine-Learning Framework Based on XGBoost–SHAP and Big Data for Revealing the Socioeconomic Drivers of Population Urbanization in China},
  author = {Ziheng Shangguan},
  year = {2025},
  journal = {Systems},
  doi = {10.3390/systems13080679},
  url = {https://doi.org/10.3390/systems13080679}
}

RIS

TY  - JOUR
TI  - An Explainable Machine-Learning Framework Based on XGBoost–SHAP and Big Data for Revealing the Socioeconomic Drivers of Population Urbanization in China
AU  - Ziheng Shangguan
PY  - 2025
JO  - Systems
DO  - 10.3390/systems13080679
UR  - https://doi.org/10.3390/systems13080679
ER  -

APA

Shangguan, Z. (2025). An Explainable Machine-Learning Framework Based on XGBoost–SHAP and Big Data for Revealing the Socioeconomic Drivers of Population Urbanization in China. Systems. https://doi.org/10.3390/systems13080679

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