This project aims to build a classifier to predict whether a loan case will be paid off or not using a historical dataset from previous loan applications, clean the data, and apply different classification algorithms on the data. The data is from the official website of Lending club and It has more than 1.6M loan entries and hundreds of features.
I applied various techniques to prevent overfitting. I did undersampling by boosting and bagging to balance the imbalance data set. In order to build the machine learning models, we need to do the data processing in advance. Firstly, dropping columns that contain too many missing values.
Based on setting different parameters to compare the optimized models with baseline models. I evaluated models with accuracy score, precision, recall and F1-score.
