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A big data analytics approach for construction firms failure prediction models
Alaka, Hafiz; Oyedele, Lukumon; Owolabi, Hakeem; … - In: IEEE transactions on engineering management : EM 66 (2019) 4, pp. 689-698
Persistent link: https://www.econbiz.de/10012129927
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Forecasting sovereign risk in the euro area via machine learning
Belly, Guillaume; Boeckelmann, Lukas; Caicedo Graciano, … - In: Journal of forecasting 42 (2023) 3, pp. 657-684
Persistent link: https://www.econbiz.de/10014292224
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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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Bankruptcy prediction using support vector machines and feature selection during the recent financial crisis
Dellepiane, Umberto; Di Marcantonio, Michele; Laghi, Enrico - In: International journal of economics and finance 7 (2015) 8, pp. 182-195
Persistent link: https://www.econbiz.de/10011346867
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Predicting corporate financial distress using data mining techniques : an application in Tehran Stock Exchange
Salehi, Mahdi; Shiri, Mahmoud Mousavi; Pasikhani, … - In: International journal of law and management : IJLMA 58 (2016) 2, pp. 216-230
Persistent link: https://www.econbiz.de/10011485759
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Social media mining for ideation : identification of sustainable solutions and opinions
Ozcan, Sercan; Suloglu, Metin; Sakar, C. Okan; … - In: Technovation : the international journal of … 107 (2021), pp. 1-12
Persistent link: https://www.econbiz.de/10013257498
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Text classification for organizational researchers : a tutorial
Kobayashi, Vladimer B.; Mol, Stefan T.; Berkers, Hannah A. - In: Organizational research methods : ORM 21 (2018) 3, pp. 766-799
Persistent link: https://www.econbiz.de/10011880171
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Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry
Gordini, Niccolò; Veglio, Valerio - In: Industrial marketing management : the international … 62 (2017), pp. 100-107
Persistent link: https://www.econbiz.de/10011707072
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Depth-based support vector classifiers to detect data nests of rare events
Dyckerhoff, Rainer; Stenz, Hartmut Jakob - In: International journal of computational economics and … 11 (2021) 2, pp. 107-142
Persistent link: https://www.econbiz.de/10012507582
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An asymptotically minimax kernel machine
Ghosh, Debashis - In: Statistics & Probability Letters 95 (2014) C, pp. 33-38
Recently, a class of machine learning-inspired procedures, termed kernel machine methods, has been extensively developed in the statistical literature. In this note, we construct a so-called ‘adaptively minimax’ kernel machine. Such a construction highlights the limits on the...
Persistent link: https://www.econbiz.de/10010939471