A Hybrid Approach for Predicting Probability of Default in Peer-to-Peer (P2P) Lending Platforms Using Mixture-of-Experts Neural Network

ISSN Print: 2327-7211
ISSN Online: 2327-7203
www.scirp.net/journal/jdaip
E-mail: [email protected]

Citations

"A Hybrid Approach for Predicting Probability of Default in Peer-to-Peer (P2P) Lending Platforms Using Mixture-of-Experts Neural Network"
written by Christopher Watitwa Makokha, Ananda Kube, Oscar Ngesa,
published by Journal of Data Analysis and Information Processing, Vol.12 No.2, 2024

has been cited by the following article(s):

No relevant information.

[1]	Large Numerical Models from a Business Perspective Synthesis Lectures on Technology Management & Entrepreneurship, 2026 DOI:10.1007/978-3-032-14869-8_5

[2]	Hybrid Deep Learning Models for Detecting Anomalous Behavior in Peer-to-Peer Payment Systems 2026 IEEE 2nd International Conference on Secure IoT, Assured and Trusted Computing (SATC), 2026 DOI:10.1109/SATC69565.2026.11542498