A machine learning project for classifying loan defaults using different models
- person_age: Age
- person_income: Annual Income
- person_home_ownership: Home ownership (MORTGAGE,OWN,RENT,OTHER)
- person_emp_length: Employment length (in years)
- loan_intent: Loan intent (DEBTCONSOLIDATION,EDUCATION,HOMEIMPROVEMENT,MEDICAL,PERSONAL,VENTURE)
- loan_grade: Loan grade (A,B,C,D,E,F,G)
- loan_amnt: Loan amount
- loan_int_rate: Interest rate
- loan_status: Loan status (0 is non default, 1 is default)
- loan_percent_income: Percent income (%)
- cb_person_default_on_file: Historical default (N is non default, Y is default)
- cb_preson_cred_hist_length: Credit history length
| Metric | Value |
|---|---|
| Total entries | 32,564 |
| Columns | 12 |
| Memory usage | 17.11+ MB |
| Data types | Mixed (int64 and object) |
🚀 In Progress
📅 Last updated: June 27, 2025
🔗 Data source: Kaggle by Lao Tse
Note: This project is currently under development. Initial dataset analysis has been completed.