Using Data Mining Techniques to Develop Models for Credit Card Payment Amounts
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Abstract
The goals of this study were to create a credit card payment amount model utilizing data mining techniques by using the following four methods: regression analysis, artificial neural networks, support vector machines for regression, and maroon peak (Model Tree: M5P). The amount of credit card payments from March 2015 to August 2022 served as the study's source of data. The experimental findings indicate that, at 7.80% of MMRE, the maroon peak (Model Tree: M5P) was the model with the highest performance for prediction.
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