The aim of the work is to predict the credit card approval using XGBoost algorithm in comparison with logistic regression to improve accuracy. Accuracy is performed with the dataset size of 48678. Prediction of credit card approval using XGboost Classifier where the number of samples (N = 10) and logistic regression where the number of samples (N = 10) algorithms. The dataset contains 19 attributes that help in whether the person gets the approval of a credit card or not. The Accuracy of XGboost Classifier is 87.97% and loss is 12.04% which appears to be better than Logistic Regression accuracy is 65.16 % and loss is 34.84 %. There is a significant difference in Accuracy (P = 0.487). Conclusion: The results show that the Novel XGboost Classifier is significantly better than Logistic Regression (LR) for Credit Card Approval Prediction in terms of accuracy.
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21 November 2023
CONTEMPORARY INNOVATIONS IN ENGINEERING AND MANAGEMENT
22–23 April 2022
Nandyal, India
Research Article|
November 21 2023
Improved accuracy in prediction of credit card approval using a novel XG boost compared with logistic regression Available to Purchase
Pathipati Yasasvi;
Pathipati Yasasvi
a)
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University
, Chennai, Tamil Nadu, 602105, India
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S. Magesh Kumar
S. Magesh Kumar
b)
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University
, Chennai, Tamil Nadu, 602105, India
b)Corresponding author: [email protected]
Search for other works by this author on:
Pathipati Yasasvi
a)
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University
, Chennai, Tamil Nadu, 602105, India
S. Magesh Kumar
b)
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University
, Chennai, Tamil Nadu, 602105, India
b)Corresponding author: [email protected]
AIP Conf. Proc. 2821, 020035 (2023)
Citation
Pathipati Yasasvi, S. Magesh Kumar; Improved accuracy in prediction of credit card approval using a novel XG boost compared with logistic regression. AIP Conf. Proc. 21 November 2023; 2821 (1): 020035. https://doi.org/10.1063/5.0166576
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