Keywords

Credit Card, Decision Tree, Machine Learning

Abstract

Nowadays, machine learning algorithms are com-
monly used by the financial institutions or bankers to evaluate
the applications’ requires for credit card. In this study, we used
the decision tree algorithm to predict credit card approval based
on the other associated features applicants like age, employment
status, Education Level, etc. Our results shows that the applicants’
Prior Default and Debt, and Employed have more contribution
in the credit card approval.

Course Name

STA 6704 Data Mining 2

Instructor Name

Rui Xie

College

College of Sciences

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Data Science Commons

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