Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning

Ma, Xiaojun; Sha, Jinglan; Wang, Dehua; Yu, Yuanbo; Yang, Qian; Niu, Xueqi

doi:10.1016/j.elerap.2018.08.002

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Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning

Author(s): Xiaojun Ma , Jinglan Sha , Dehua Wang , Yuanbo Yu , Qian Yang , Xueqi Niu

Publication date Created: September 2018

Publication date (Print): September 2018

Journal: Electronic Commerce Research and Applications

Publisher: Elsevier BV

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Title: Electronic Commerce Research and Applications

Abbreviated Title: Electronic Commerce Research and Applications

Publisher: Elsevier BV

ISSN (Print): 15674223

Publication date Created: September 2018

Publication date (Print): September 2018

Volume: 31

Pages: 24-39

Article

DOI: 10.1016/j.elerap.2018.08.002

SO-VID: b716fb0c-6c34-4aba-9e0a-8ee9d4442d52

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https://www.elsevier.com/tdm/userlicense/1.0/

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Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning

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