Review of Domestic Application Research of Big Data Mining Technology-SVM in Credit Risk Evaluation
Mu Zhang, Lu-jing Pang
Available Online January 2019.
- https://doi.org/10.2991/seiem-18.2019.64How to use a DOI?
- big data mining technology; support vector machine; credit risk; credit risk Evaluation; Journals reviewed
- As a classification model in large data mining technology, support vector machine (SVM) has been developing and improving continuously, it has been applied to the field of credit risk more and more widely. The effective evaluation of credit risk by support vector machine is beneficial to the development of banks and enterprises. This paper mainly combs the domestic literature from three aspects: data preprocessing, application and improvement, and integrated combination discrimination of support vector machine in credit risk assessment. Finally, a brief review based on the domestic literature is made. Through the collation of journals reviewed, we can better understand the specific application status of support vector machine in the field of credit risk and lay the foundation for the follow-up research work.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Mu Zhang AU - Lu-jing Pang PY - 2019/01 DA - 2019/01 TI - Review of Domestic Application Research of Big Data Mining Technology-SVM in Credit Risk Evaluation BT - 3rd International Seminar on Education Innovation and Economic Management (SEIEM 2018) PB - Atlantis Press SN - 2352-5398 UR - https://doi.org/10.2991/seiem-18.2019.64 DO - https://doi.org/10.2991/seiem-18.2019.64 ID - Zhang2019/01 ER -