Loan prediction machine learning project

In this python machine learning project, I built a binary classifier using the 3 algorithms to predict the loan status. Through this project, I applied techniques to address loan status imbalance issues and achieved an accuracy of more than 60%. The random forest model yields a very good performance as indicated by the model accuracy which was found to be 78.472222%. Credit_History is a very important variable because of its high correlation with Loan_Status, therefore, showing high Dependancy for the latter. To address the issue of loan status imbalance problem, we used the oversampling technique, this was done by the SMOTE package imported from the imblearn module. ROC AUC of our models approaches towards 1. So, we can conclude that our classifier does a good job of predicting whether a loan will be approved or not.