Data and Python code for: Modeling Central Bank Digital Currency Implementation Factors Using Support Vector Machines
Abstract
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.
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 January 2026
- Language
- EN
- Document type
- Dataset