Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

Pławiak, Paweł, Abdar, Moloud and Acharya, U. Rajendra 2019, Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring, Applied Soft Computing Journal, vol. 84, pp. 1-14, doi: 10.1016/j.asoc.2019.105740.

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Title Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring
Author(s) Pławiak, Paweł
Abdar, MoloudORCID iD for Abdar, Moloud orcid.org/0000-0002-3059-6357
Acharya, U. Rajendra
Journal name Applied Soft Computing Journal
Volume number 84
Article ID 105740
Start page 1
End page 14
Total pages 14
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2019-11
ISSN 1568-4946
Keyword(s) Credit scoring
Credit risk
Data mining
Machine learning
Ensemble learning
Deep learning
Genetic algorithms
Feature selection and extraction
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
Computer Science
CONVOLUTIONAL NEURAL-NETWORK
CLASSIFICATION ALGORITHMS
BANKRUPTCY PREDICTION
AUTOMATED DETECTION
FEATURE-SELECTION
MINING APPROACH
OPTIMIZATION
SYSTEM
MODEL
ARCHITECTURES
Language eng
DOI 10.1016/j.asoc.2019.105740
Indigenous content off
Field of Research 0102 Applied Mathematics
0801 Artificial Intelligence and Image Processing
0806 Information Systems
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30134108

Document type: Journal Article
Collection: Deputy Vice-Chancellor Research Group
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