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



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