Can machine learning paradigm improve attribute noise problem in credit risk classification?
Lean Yu, Xiaowen Huang, Hang Yin
| Year of publication: |
2020
|
|---|---|
| Authors: | Yu, Lean ; Huang, Xiaowen ; Yin, Hang |
| Published in: |
International review of economics & finance : IREF. - Amsterdam [u.a.] : Elsevier, ISSN 1059-0560, ZDB-ID 1137476-7. - Vol. 70.2020, p. 440-455
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| Subject: | Attribute noise | Credit risk classification | Dual voting | Learning strategy | Machine learning | Sparseness | Künstliche Intelligenz | Artificial intelligence | Kreditrisiko | Credit risk | Klassifikation | Classification | Theorie | Theory | Lernprozess | Learning process |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.iref.2020.08.016 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012486810