Credit risk assessment with a multistage neural network ensemble learning approach
By Lean Yu, Shouyang Wang, Kin Keung Lai. Expert systems with applications, 2008
323 citations recorded by the source corpus.
Subfields: Accounting, Artificial Intelligence, Civil and Structural Engineering
View Paper: https://www.semanticscholar.org/paper/a0d28af34f2fa8f5b9140f630cd7ae872df72c4f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Stefan Lessmann
- Lyn C. Thomas
- Hsin-Vonn Seow
- Quyen Ho
- Thanh Duong
- K. Tran
- Bart Baesens
- Kush R. Varshney
In Artificial Intelligence
- Stefan Lessmann
- Lyn C. Thomas
- Hsin-Vonn Seow
- Quyen Ho
- Thanh Duong
- K. Tran
- Bart Baesens
- Kush R. Varshney
In Civil and Structural Engineering
Citations in the corpus
- Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015, background): “Last, only two studies employ selective ensembles and they use rather simple approaches (Yu, et al., 2008; Zhou, et al., 2010).”
- Credit scoring model: A combination of genetic programming and deep learning (2016, methodology): “25] A2 [0, 28] A3 [1, 3] A4 [1, 14] A5 [1, 9] A6 [0, 28.”