Loan Default Prediction

Abstract

Built an ensemble model comprising of - tuned SVM, MLP, Random Forests, Extra Trees Classifier and KNN models, to identify loan defaulting with an accuracy of 99%. Identified key features that are essential for prediction, performed Random Forest based data imputation and SMOTE Oversampling based data generation.