- 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
- Programming Language: Python
- Libraries: Pandas, Scikit-learn, Matplotlib, Seaborn
https://www.lendingclub.com/info/download-data.action