Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending

Yanka Aleksandrova

Детайли

Източник: TEM Journal - Technology, Education, Management, Informatics / Association for Information Communication Technology Education and Science
Издателство: UIKTEN-Assoc. for Inform. Communication Technology
Местоиздаване: Novi Pazar, Serbia
Година на издаване: 2021
Страници: pp. 133-143
Том: 10
Ключови думи: machine learning, peer-to-peer lending (P2P), credit scoring, ensemble classifiers, XGBoost

ISBN: ISSN 2217-8309 (print) ; 2217-8333 (online)
Пор.№: 1, February

Действия

MLA (7th edition) Chicago / Turabian (16th edition) Harvard

Aleksandrova, Yanka Georgieva Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending, UIKTEN-Assoc. for Inform. Communication Technology, 2021, pp. 133-143, ISSN 2217-8309 (print) ; 2217-8333 (online).

Aleksandrova, Yanka Georgieva . Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending. Novi Pazar, Serbia: UIKTEN-Assoc. for Inform. Communication Technology, 2021, pp. 133-143, ISSN 2217-8309 (print) ; 2217-8333 (online).

Aleksandrova, Yanka Georgieva (2021) Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending, Novi Pazar, Serbia: UIKTEN-Assoc. for Inform. Communication Technology, pp. 133-143, ISSN 2217-8309 (print) ; 2217-8333 (online)

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Comparing Performance of Machine Learning Algorithms for Default Risk Prediction in Peer to Peer Lending

Детайли

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Действия