Analyzing-Credit-Risk-Determinants-A-Machine-Learning-Approach-Using-Armenian-Credit-Registry-Data
anahithakobyan1/Analyzing-Credit-Risk-Determinants-A-Machine-Learning-Approach-Using-Armenian-Credit-Registry-Data
Application of machine learning methods to determine the key parameters influencing default probabilities among bank customers in Armenia
Summary
A machine learning project analyzing Armenian credit registry data to predict loan defaults using logistic regression, random forest, and XGBoost models. The repository contains Jupyter notebooks for data cleaning, preprocessing, and modeling, with evaluation based on standard ML metrics.