top of page

TEAM

Credit Card Default Prediction

Shirin provat, Brad Mostowski, Munawar Ali, Ayoub Lassoued, Martin Molina-Fructuoso

clear.png

We fitted models of Logistic Regression, Naive Bayes, Random Forest, KNN classifier, and Neural Networks to credit card consumer data to predict payment default. With Neural Networks, we attempted a novel architecture which exploited the partially sequential nature of the given data. Using both accuracy and a metric called "area ratio" to gauge prediction confidence, we compared the models to figure out which one was best.

Dataset: https://archive.ics.uci.edu/ml/machine-learning-databases/00350/

Screen Shot 2022-06-03 at 11.31.35 AM.png
github URL

©2017-2025 by The Erdős Institute.

bottom of page