Logistic and SVM Credit Score Models Based on Lasso Variable Selection

ISSN Print: 2327-4352
ISSN Online: 2327-4379
www.scirp.net/journal/jamp
E-mail: [email protected]

Citations

"Logistic and SVM Credit Score Models Based on Lasso Variable Selection"
written by Qingqing Li,
published by Journal of Applied Mathematics and Physics, Vol.7 No.5, 2019

has been cited by the following article(s):

[1]	Prediction of personal default risk based on a sparrow search algorithm with supportive vector machine model
	Mathematical Biosciences and Engineering, 2023

[2]	An interpretable decision tree ensemble model for imbalanced credit scoring datasets
	Journal of Intelligent & Fuzzy Systems, 2023

[3]	Investigation on the Effect of Household Income and Demographic Factors on Healthcare Cost in Perak
	Proceedings of the 7th International Conference on …, 2022

[4]	The application of machine learning in bank credit rating prediction and risk assessment
	2021

[5]	Prognostic Model to Predict Postoperative Adverse Events in Pediatric Patients With Aortic Coarctation
	2021

[1]	Meta‐Learning Credit Risk Prediction by Fusing Regularized Logistic Regression and Random Forest Journal of Forecasting, 2026 DOI:10.1002/for.70097

[2]	An interpretable decision tree ensemble model for imbalanced credit scoring datasets Journal of Intelligent & Fuzzy Systems, 2023 DOI:10.3233/JIFS-230825

[3]	Efficient Commercial Bank Customer Credit Risk Assessment Based on LightGBM and Feature Engineering 2023 5th International Symposium on Smart and Healthy Cities (ISHC), 2023 DOI:10.1109/ISHC61216.2023.00022

[4]	Proceedings of the 7th International Conference on the Applications of Science and Mathematics 2021 Springer Proceedings in Physics, 2022 DOI:10.1007/978-981-16-8903-1_24

[5]	Prognostic Model to Predict Postoperative Adverse Events in Pediatric Patients With Aortic Coarctation Frontiers in Cardiovascular Medicine, 2021 DOI:10.3389/fcvm.2021.672627

[6]	The application of machine learning in bank credit rating prediction and risk assessment 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), 2021 DOI:10.1109/ICBAIE52039.2021.9389901