Credit Car Application Result Prediction Model

In this project, I programmed a Machine Learning Model using MATLAB to predict the result of credit card applications by analyzing the user data of applicants.

I applied feature normalization and hyperparameter tuning; raised Perceptron test accuracy from 67.97% to 82.35%.

I also applied k-NN(Mahalanobis) model and boosted test accuracy from 82.35% to 86.27%.

I co-authored an academic paper on machine learning credit risk prediction, currently under final revision for publication.