P2P Borrower Default Identification and Prediction Based on RFE-Multiple Classification Models

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ISSN Print: 2329-3284
ISSN Online: 2329-3292
www.scirp.org/journal/ojbm
E-mail: ojbm@scirp.org

"P2P Borrower Default Identification and Prediction Based on RFE-Multiple Classification Models"
written by Xianyan Hou,
published by Open Journal of Business and Management, Vol.8 No.2, 2020

has been cited by the following article(s):

[1]	Detection of Defaulters in P2P Lending Platforms using Unsupervised Learning
	2022 IEEE International Conference on …, 2022

[2]	Identifying and predicting default borrowers in P2P lending platform: A machine learning approach
	2021 IEEE International …, 2021

[3]	Challenges of Financial Risk Management: AI Applications
	2021

[4]	Peer-to-peer lending loan default prediction: machine learning classification algorithms applied to Lending Club data, investors' perspective
	2020

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