A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation-Reference-Cited by-同舟云学术

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A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation

Published:2019-07 Issue: Volume:526 Page:121073
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Shen Feng,Zhao Xingchao,Li Zhiyong,Li Ke,Meng Zhiyi

Funder

Humanities and Social Sciences Foundation of the Ministry of Education of China

Soft Science Program of Sichuan Province

Fundamental Research Funds for the Central Universities

Research Center for System Sciences and Enterprise Development

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference45 articles.

1. Statistical classification methods in consumer credit scoring: a review;Hand;J. Roy. Statist. Soc. Ser. A,1997

2. Recent developments in consumer credit risk assessment;Crook;European J. Oper. Res.,2007

3. Learning from class-imbalanced data: Review of methods and applications;Haixianga;Expert Syst. Appl.,2017

4. A new hybrid ensemble credit scoring model based on classifiers consensus system approach;Ala’raj;Expert Syst. Appl.,2016

5. A stable systemic risk ranking in China’s banking sector: Based on principal component analysis;Fang;Physica A,2018

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