TITLE:
The P2P Risk Assessment Model Based on the Improved AdaBoost-SVM Algorithm
AUTHORS:
Jianhui Yang, Dongsheng Luo
KEYWORDS:
Peers-to-Peers, AdaBoost, SVM, The Combinations of Learning Machine, Rule Sampling
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.6 No.2,
June
27,
2017
ABSTRACT: The improved AdaBoost-SVM algorithm is used to classify the safety and the risk from the Peers-to-Peers net loan platforms. Since the SVM algorithm is hard to deal with the rare samples and its training is slow, rule sampling is used to reduce the classify noise. Then, with the combinations of learning machine, P2P risks can be identified. The result shows that IAdaBoost algorithm can improve the risk platform classification accuracy. And the error of classification can be controlled in 5%.