Credit Risk Models for Financial Fraud Detection: A New Outlier Feature Analysis Method of XGBoost With SMOTE Journal Article

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MLA

Xia, Huosong, et al. "Credit Risk Models for Financial Fraud Detection: A New Outlier Feature Analysis Method of XGBoost With SMOTE." JDM vol.34, no.1 2023: pp.1-20. http://doi.org/10.4018/JDM.321739

APA

Xia, H., An, W., & Zuopeng (Justin) Zhang. (2023). Credit Risk Models for Financial Fraud Detection: A New Outlier Feature Analysis Method of XGBoost With SMOTE. Journal of Database Management (JDM), 34(1), 1-20. http://doi.org/10.4018/JDM.321739

Chicago

Xia, Huosong, Wuyue An, and Zuopeng (Justin) Zhang. "Credit Risk Models for Financial Fraud Detection: A New Outlier Feature Analysis Method of XGBoost With SMOTE," Journal of Database Management (JDM) 34, no.1: 1-20. http://doi.org/10.4018/JDM.321739

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Credit Risk Models for Financial Fraud Detection: A New Outlier Feature Analysis Method of XGBoost With SMOTE

Journal of Database Management (JDM)

The Journal of Database Management (JDM) publishes original research on all aspects of database management, systems analysis and design, and software engineering. The primary mission of JDM is to be instrumental in the improvement and development of theory and practice related to information technology and management of information resources. The journal is targeted at both academic researchers and practicing IT professionals.
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