DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring-Reference-Cited by-同舟云学术

DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring

Published:2020-04 Issue: Volume:516 Page:401-418
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Pławiak Paweł^ORCID,Abdar Moloud,Pławiak Joanna,Makarenkov Vladimir,Acharya U Rajendra

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. A comparative study on base classifiers in ensemble methods for credit scoring;Abelln;Expert Syst. Appl.,2017

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

3. Improving credit scoring by differentiating defaulter behaviour;Bravo;J. Oper. Res. Soc.,2015

4. Reject inference in consumer credit scoring with nonignorable missing data;Bcker;J. Banking Finance,2013

5. An artificial immune classifier for credit scoring analysis;Chang;Appl. Soft Comput.,2012

Cited by 111 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dual-Level Decision Tree-Based Model for Dispersed Data Classification;International Conference on Information Systems Development;2024-09-09

2. ISSLEDOVANIE STRATEGIChESKIKh POSLEDSTVIY UTEChKI SKORINGOVOY MODELI;Автоматика и телемеханика;2024-08-15

3. Comparison of the impact of dimensionality reduction and data splitting on classification performance in credit risk assessment;Artificial Intelligence Review;2024-08-13

4. A semi-supervised reject inference framework with hierarchical heterogeneous networks for credit scoring;International Journal of Forecasting;2024-08

5. The Study of the Strategic Consequences of a Scoring Model Disclosure;Automation and Remote Control;2024-08