| Column Name | Meaning | Explanation (Simple) | Example |
|---|---|---|---|
| Loan_ID | Loan Identifier | Unique ID for each loan application | LP001002 |
| Gender | Applicant’s Gender | Whether the applicant is Male or Female | Male, Female |
| Married | Marital Status | Whether the applicant is married or not | Yes, No |
| Dependents | Number of Dependents | Number of people dependent on the applicant (kids, family) | 0, 1, 2, 3+ |
| Education | Education Level | Applicant’s education background | Graduate, Not Graduate |
| Self_Employed | Employment Type | Whether the applicant is self-employed or not | Yes, No |
| ApplicantIncome | Applicant’s Income | Monthly income of the main applicant | 5000 |
| CoapplicantIncome | Co-applicant’s Income | Monthly income of co-applicant (e.g., spouse) | 2000 |
| LoanAmount | Loan Amount | Amount of loan applied (in thousands) | 128 = 128,000 |
| Loan_Amount_Term | Loan Term | Time period of the loan (in months) | 360 months = 30 years |
| Credit_History | Credit History | Record of applicant’s past credit repayment (1 = good, 0 = bad) | 1, 0 |
| Property_Area | Property Location | Area type where the property is located | Urban, Semiurban, Rural |
| Loan_Status | Target Variable | Whether the loan was approved or not | Y = Approved, N = Not Approved |
| Model | Accuracy |
|---|---|
| Logistic Regression (Base) | 78% |
| Logistic Regression (L1) | 78% |
| Logistic Regression (L2) | 78% |
| Logistic Regression (Tuned) | 78% |
| Decision Tree (Gini) | 74% |
| Decision Tree (Entropy) | 75% |
| Decision Tree (Tuned) | 76% |
| Random Forest (Base) | 78% |
| Random Forest (Tuned) | 78% |
| AdaBoost (Base) | 79% |
| AdaBoost (Tuned) | 78% |
| SVM (Base) | 79% |
| SVM (Tuned) | 78% |
Best Model (in my opinion):
Adam without grid search, because it gives the lowest False Positives (FP = 34), which is my main concern.