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Credit Card Default Prediction

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


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.


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