@inproceedings{5d3600822f5e4007b22e3c4fd3ed8d94,
title = "A PSO-based ensemble model for peer-to-peer credit scoring",
abstract = "We propose a multi-classifier ensemble model based on particle swarm optimization (PSO) for the evaluation of personal credit risk in peer-to-peer (P2P) lending platforms. In the proposed method, we consider the differences and complementarity of the base classifiers' performance and use PSO to optimize their weights. Experimental results show that our proposed P2P personal credit scoring model outperforms both single and other benchmark ensemble models. Among the examined model variants, the ensemble model based on PSO with 100 particles is the best.",
keywords = "Credit Scoring, Ensemble Models, P2P Online Lending, Particle Swarm Optimization",
author = "Chaoqun Wang and Raymond Chiong and Yuan Chen and Zhongyi Hu and Sandeep Dhakal and Yukun Bao",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018 ; Conference date: 28-07-2018 Through 30-07-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/FSKD.2018.8687154",
language = "English",
series = "ICNC-FSKD 2018 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "412--418",
editor = "Zheng Xiao and Lipo Wang and Guoqing Xiao and Xiong Ning and Kenli Li and Maozhen Li",
booktitle = "ICNC-FSKD 2018 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery",
}