LoanDefault Prediction Save Abandoned
Lending Club Loan data analysis
Project README
LoanDefault-Prediction
Model Accuracies:
| Model | Accuracy |
|---|---|
| Random Forest with Randomized search CV | 82.09 |
| Logistic Regression with Grid search CV | 83.18 |
| Support Vector Machine with Grid search CV | 82.50 |
| K Nearest Neighbors with Grid search CV | 77.40 |
| Bagging with Base estimator as Random Forest | 84.10 |
| Bagging with Base estimator as Logistic Regression | 83.10 |
| AdaBoost Classifier | 83.60 |
| MultilLayer Perceptron Classifier | 83.40 |
check out our project report to find out why we used these models
Technologies:
- Programming Language: Python
- Libraries: Pandas, Scikit-learn, Matplotlib, Seaborn
- Visualization: plotly
Data Source:
Open Source Agenda is not affiliated with "LoanDefault Prediction" Project. README Source: harishpuvvada/LoanDefault-Prediction
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