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  • Search: subject:"Extreme Gradient Boosting"
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Year of publication
Subject
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Forecasting model 21 Prognoseverfahren 21 Artificial intelligence 15 Künstliche Intelligenz 15 Extreme gradient boosting 9 Machine learning 8 Insolvency 6 Insolvenz 6 Theorie 6 Theory 6 extreme gradient boosting 6 Extreme Gradient Boosting 5 Neural networks 5 Neuronale Netze 5 machine learning 5 Algorithm 3 Algorithmus 3 Industry 4.0 3 Mustererkennung 3 Pattern recognition 3 artificial intelligence 3 eXtreme Gradient Boosting (XGBoost) 3 high-tech companies 3 random forest 3 robotics 3 Bank failure 2 Bank failure prediction 2 Bank failure prevention 2 Bankinsolvenz 2 Beziehungsmarketing 2 Coronavirus 2 Credit rating 2 Croatia 2 Decomposition method 2 Dekompositionsverfahren 2 Early warning system 2 Emissions trading 2 Emissionshandel 2 Ensemble 2 Extreme gradient boosting tree 2
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Online availability
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Undetermined 19 Free 13 CC license 6
Type of publication
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Article 27 Book / Working Paper 5
Type of publication (narrower categories)
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Article in journal 24 Aufsatz in Zeitschrift 24 Working Paper 5 Arbeitspapier 3 Graue Literatur 3 Non-commercial literature 3 Article 2 research-article 1
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Language
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English 32
Author
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Carmona, Pedro 3 Grebenar, Tomislav 3 Hrbić, Rajka 3 Brédart, Xavier 2 Jiang, Ping 2 Kumar, Pradeep 2 Liu, Zhenkun 2 Momparler, Alexandre 2 Musa, Mohamed 2 Nicodemo, Catia 2 Niu, Xinsong 2 Oreffice, Sonia 2 Quintana-Domeque, Climent 2 Shetty, Shekar 2 Wan, Chunzhuo 2 Wang, Jianzhou 2 Wang, Ping 2 Zhang, Lifang 2 Zhu, Bangzhu 2 Abdelmoniem, Ahmed M. 1 Abedin, Mohammad Zoynul 1 Adland, Roar 1 Akyildirim, Erdinc 1 Alvarez González, Francisco 1 Bairagi, Anupam Kumar 1 Barth, Michael 1 Bellotti, Anthony Graham 1 Boulougouris, Evangelos 1 Cajias, Marcelo 1 Cepni, Oguzhan 1 Chevallier, Julien 1 Climent Diranzo, Francisco J. 1 Climent, Francisco 1 Clintworth, Mark 1 Corbet, Shaen 1 Cui, Tianxiang 1 De Bock, Koen W. 1 Ding, Shusheng 1 Du, Zhiyuan 1 Emrich, Eike 1
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Published in...
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Computational economics 2 Finance research letters 2 Journal of Risk and Financial Management 2 Journal of risk and financial management : JRFM 2 Academia : revista Latinoamericana de administración 1 Corporate governance : international journal of business in society 1 Decision analytics journal 1 Discussion paper series / IZA 1 Diskussionspapiere des Europäischen Instituts für Sozioökonomie e.V. 1 Energy economics 1 IZA Discussion Papers 1 International journal of contemporary hospitality management 1 International journal of production research 1 International review of economics & finance : IREF 1 International review of financial analysis 1 Journal of European Real Estate Research 1 Journal of business research : JBR 1 Journal of economy and technology 1 Journal of forecasting 1 Maritime economics & logistics 1 Maritime policy & management 1 Mokslo darbai / Vilniaus Universitetas 1 Risks : open access journal 1 Technological forecasting and social change : an international journal 1 The journal of real estate finance and economics 1 Transportation research / E : an international journal 1 Working paper / Department of Economics, Copenhagen Business School 1 Working papers / Croatian National Bank 1
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Source
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ECONIS (ZBW) 27 EconStor 4 Other ZBW resources 1
Showing 1 - 10 of 32
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Machine Learning and Multiple Abortions
Kumar, Pradeep; Nicodemo, Catia; Oreffice, Sonia; … - 2024
in the highest risk decile, capturing about 55% of cases, whereas linear models and Extreme Gradient Boosting excel in …This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient … Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and …
Persistent link: https://www.econbiz.de/10015045482
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A generalized linear model and machine learning approach for predicting the frequency and severity of cargo insurance in Thailand's border trade context
Praiya Panjee; Sataporn Amornsawadwatana - In: Risks : open access journal 12 (2024) 2, pp. 1-33
to comprehensively assess predictive performance. For frequency prediction, extreme gradient boosting (XGBoost … slightly higher MAE. For severity prediction, extreme gradient boosting (XGBoost) displays the lowest MAE, implying better … error magnitudes despite a higher MAE. In conclusion, extreme gradient boosting (XGBoost) stands out in mean absolute error …
Persistent link: https://www.econbiz.de/10014497395
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Machine learning and multiple abortions
Kumar, Pradeep; Nicodemo, Catia; Oreffice, Sonia; … - 2024
in the highest risk decile, capturing about 55% of cases, whereas linear models and Extreme Gradient Boosting excel in …This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient … Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and …
Persistent link: https://www.econbiz.de/10014545133
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Predicting mortgage loan defaults using machine learning techniques
Krasovytskyi, Danylo; Stavytskyy, Andriy - In: Mokslo darbai / Vilniaus Universitetas 103 (2024) 2, pp. 140-160
oversampling technique and compared the results. It was found that random forest and extreme gradient-boosting decision trees are …
Persistent link: https://www.econbiz.de/10015047688
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A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction
Hassan, Md. Mehedi; Hassan, Md. Mahedi; Yasmin, Farhana; … - In: Decision analytics journal 7 (2023), pp. 1-17
) approach, which selects the most important attributes. Logistic Regression (LR), K-Nearest Neighbors (KNN), Extreme Gradient … Boosting (XGB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM …
Persistent link: https://www.econbiz.de/10014497358
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A meta-learning based stacked regression approach for customer lifetime value prediction
Gadgil, Karan; Gill, Sukhpal Singh; Abdelmoniem, Ahmed M. - In: Journal of economy and technology 1 (2023), pp. 197-207
Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue, and this could be achieved only by understanding the customers more. Customer lifetime value (CLV) is the total monetary value of transactions or purchases made by a customer with the...
Persistent link: https://www.econbiz.de/10014555514
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Interval forecasting of carbon price with a novel hybrid multiscale decomposition and bootstrap approach
Zhu, Bangzhu; Wan, Chunzhuo; Wang, Ping; Chevallier, Julien - In: Journal of forecasting 44 (2025) 2, pp. 376-390
Persistent link: https://www.econbiz.de/10015374041
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Assessment of readiness of Croatian companies to ontroduce I4.0 technologies
Hrbić, Rajka; Grebenar, Tomislav - In: Journal of Risk and Financial Management 15 (2022) 12, pp. 1-24
indicators of a sample of 58 identified I4.0 companies. We developed a machine-learning model by using the eXtreme Gradient … Boosting algorithm (XGBoost) for this purpose, an approach that has not been used in any similar research. This research shows …
Persistent link: https://www.econbiz.de/10014332714
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Bankruptcy prediction using machine learning techniques
Shetty, Shekar; Musa, Mohamed; Brédart, Xavier - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-10
In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost …
Persistent link: https://www.econbiz.de/10013201339
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Bankruptcy prediction using machine learning techniques
Shetty, Shekar; Musa, Mohamed; Brédart, Xavier - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-10
In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost …
Persistent link: https://www.econbiz.de/10012814176
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