Data and Python code for: Modeling Central Bank Digital Currency Implementation Factors Using Support Vector Machines

This deposit contains the dataset and computational materials used in the study “Modeling Central Bank Digital Currency Implementation Factors Using Support Vector Machines”. The Excel file includes structured data on central bank digital currency (CBDC) projects and country-level indicators used for classification modelling. The Jupyter Notebook contains all data preprocessing steps, model training using the Support Vector Machine (SVM) method, hyperparameter tuning, performance evaluation, and SHAP-based model interpretation. These materials are provided to ensure transparency, reproducibility, and validation of the research results.本存档包包含研究《基于支持向量机建模央行数字货币落地影响因素（Modeling Central Bank Digital Currency Implementation Factors Using Support Vector Machines）》所使用的数据集与计算材料。 该Excel文件包含用于分类建模的央行数字货币（Central Bank Digital Currency，CBDC）项目结构化数据与国家级指标数据。该Jupyter笔记本（Jupyter Notebook）包含全部数据预处理流程、基于支持向量机（Support Vector Machine，SVM）的模型训练、超参数调优、模型性能评估以及基于SHAP的模型可解释性分析。 本材料的提供旨在保障研究成果的透明度、可复现性与可验证性。