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  • Search: subject:"Boosting method"
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Year of publication
Subject
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Insolvency 2 Insolvenz 2 Asymmetric mislabeling mechanism 1 Bayes error rate 1 Boosting method 1 Computational Intelligence 1 Evolutionary algorithm 1 Evolutionärer Algorithmus 1 Financial distress prediction 1 Financial market 1 Financial network 1 Finanzmarkt 1 Firm performance 1 Forecasting model 1 Genetic algorithm 1 Gradient boosting method 1 Improved Boosting Method 1 Network-based variable 1 Prognoseverfahren 1 Robustness 1 Stakeholder 1 Theorie 1 Theory 1 Unsteady Nonlinear Aerodynamics 1 Unternehmenserfolg 1 Wind Tunnel 1 boosting method 1 business failure 1 relative importance 1 stakeholder 1
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Online availability
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Undetermined 4
Type of publication
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Article 4
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2
Language
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English 3 Undetermined 1
Author
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Alfaro-Cortés, Esteban 1 Hayashi, Kenichi 1 Li, Yongli 1 Liu, Jiaming 1 Luo, Guiming 1 Manzaneque, Monserrat 1 Priego de la Cruz, Alba María 1 Wu, Chong 1 Zhao, Boxu 1 Zhu, Jihong 1
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Published in...
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Computational Statistics 1 Computational economics 1 International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 1 Revista de contabilidad : RC-SAR 1
Source
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ECONIS (ZBW) 2 RePEc 1 Other ZBW resources 1
Showing 1 - 4 of 4
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Understanding the stakeholders' role in a business failure situation : an empirical boosting approach
Priego de la Cruz, Alba María; Alfaro-Cortés, Esteban; … - In: Revista de contabilidad : RC-SAR 23 (2020) 1, pp. 113-126
Persistent link: https://www.econbiz.de/10012173510
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Improving financial distress prediction using financial network-based information and GA-based gradient Boosting method
Liu, Jiaming; Wu, Chong; Li, Yongli - In: Computational economics 53 (2019) 2, pp. 851-872
Persistent link: https://www.econbiz.de/10012134893
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Improved Boosting Model for Unsteady Nonlinear Aerodynamics based on Computational Intelligence
Luo, Guiming; Zhao, Boxu; Zhu, Jihong - In: International Journal of Cognitive Informatics and … 11 (2017) 1, pp. 46-59
The large-amplitude-oscillation experiment was carried out with two levels of freedom to provide data. Based on the wind tunnel data, polynomial regression, least-square support vector machines and radial basis function neural networks are studied and compared in this paper. An improved model...
Persistent link: https://www.econbiz.de/10012043680
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A boosting method with asymmetric mislabeling probabilities which depend on covariates
Hayashi, Kenichi - In: Computational Statistics 27 (2012) 2, pp. 203-218
Persistent link: https://www.econbiz.de/10010558265
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