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Cost-sensitive semi-supervised selective ensemble model for customer credit scoring

  • Published:2020-02 Issue: Volume:189 Page:105118
  • ISSN:0950-7051
  • Container-title:Knowledge-Based Systems
  • language:en
  • Short-container-title:Knowledge-Based Systems

Author:

Xiao Jin,Zhou Xu,Zhong Yu,Xie Ling,Gu Xin,Liu Dunhu

Funder

Major Project of the National Social Science Foundation of China

Tianfu Ten-thousand Talents Program of Sichuan Province

National Natural Science Foundation of China

Excellent Youth Fund of Sichuan University

Leading Cultivation Talents Program of Sichuan University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference67 articles.

1. Imbalanced enterprise credit evaluation with DTE-SBD: Decision tree ensemble based on smote and bagging with differentiated sampling rates;Sun;Inform. Sci.,2018

2. Financial credit risk assessment: a recent review;Chen;Artif. Intell. Rev.,2016

3. Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research;Lessmann;European J. Oper. Res.,2015

4. The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation;Anderson,2007

5. Technology credit scoring model with fuzzy logistic regression;Sohn;Appl. Soft Comput.,2016

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