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An investigation of the effect of variable reduction on classification accuracy rates of consumer loans
Zurada, Jozef - In: Review of business information systems 17 (2013) 4, pp. 135-139
Persistent link: https://www.econbiz.de/10010231895
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HHT-based classification of composite power quality events
Saxena, D.; Singh, S. N.; Verma, K. S.; Singh, Shiv K. - In: International journal of energy sector management : IJESM 8 (2014) 2, pp. 146-159
Persistent link: https://www.econbiz.de/10010379441
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A comparative analysis of machine learning algorithms for image classification : evaluating performance
Kapse, Manohar; Elangovan, N.; Lalkiya, M.; Deshpande, … - In: Data-Driven Decision Making, (pp. 59-75). 2024
Persistent link: https://www.econbiz.de/10014633436
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Predicting the likelihood of dividend payment from Indonesian public companies with data mining methods
Kosala, Raymond - In: International journal of business information systems : … 26 (2017) 2, pp. 139-150
Persistent link: https://www.econbiz.de/10011856393
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A new approach to testing credit rating of financial debt issuers
O'Neill, T. J.; Penm, Jack H. W. - In: International journal of services and standards 3 (2007) 4, pp. 390-401
Persistent link: https://www.econbiz.de/10003603256
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Realizing the effects of trust and personality in cross functional teams using ANFIS classification framework
Krishankumar, R.; Ravichandran, K. S. - In: Computational and mathematical organization theory 24 (2018) 2, pp. 243-276
Persistent link: https://www.econbiz.de/10011856240
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Recognition and classification of single and concurrent unnatural patterns in control charts via neural networks and fitted of samples
Lesany, S. A.; Koochakzadeh, A.; Fatemi Ghomi, S. M. T. - In: International journal of production research 52 (2014) 6, pp. 1771-1786
Persistent link: https://www.econbiz.de/10010257293
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Combination forecasts of tourism demand with machine learning models
Claveria, Oscar; Monte, Enric; Torra, Salvador - In: Applied economics letters 23 (2016) 4/6, pp. 428-431
Persistent link: https://www.econbiz.de/10011430763
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Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison
Horák, Jakub; Vrbka, Jaromir; Suler, Petr - In: Journal of risk and financial management : JRFM 13 (2020) 3/60, pp. 1-15
to create a model for predicting potential bankruptcy of companies using suitable classification methods, namely Support …. For the application of classification methods, TIBCO's Statistica software, version 13, is used. In total, 6 models were …
Persistent link: https://www.econbiz.de/10012302458
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Two-dimensional face surface analysis using facial feature points detection approaches
Ahdid, Rachid; Azougaghe, Es-said; Safi, Said; Manaut, … - In: Journal of electronic commerce in organizations : the … 16 (2018) 1, pp. 57-71
Persistent link: https://www.econbiz.de/10011809544