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  • Search: subject:"Supervised Machine Learning"
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Year of publication
Subject
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Künstliche Intelligenz 44 Artificial intelligence 42 supervised machine learning 33 Supervised machine learning 22 Forecasting model 12 Prognoseverfahren 12 LASSO 7 Supervised Machine Learning 7 Theorie 7 Theory 7 Algorithm 6 Algorithmus 6 biological age 6 epigenetics 6 Classification 5 Klassifikation 5 Social Web 5 Social web 5 Aging population 4 Alternde Bevölkerung 4 Big data 4 Consumer behaviour 4 Data Mining 4 Data mining 4 Global Compact for Migration 4 Konsumentenverhalten 4 Social media 4 United Nations 4 health care utilisation 4 red herring hypothesis 4 Age group 3 Altersgruppe 3 Big Data 3 Gesundheitsversorgung 3 Health care 3 Random Forest 3 Risk management 3 binary classification 3 conditional inference trees 3 correlated predictors 3
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Online availability
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Free 39 Undetermined 26 CC license 6
Type of publication
All
Article 42 Book / Working Paper 23
Type of publication (narrower categories)
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Article in journal 30 Aufsatz in Zeitschrift 30 Working Paper 21 Graue Literatur 15 Non-commercial literature 15 Arbeitspapier 13 Article 6 research-article 2 Aufsatz im Buch 1 Book section 1
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Language
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English 60 German 4 Undetermined 1
Author
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Davillas, Apostolos 7 Jones, Andrew M. 7 Ecker-Ehrhardt, Matthias 4 Ollech, Daniel 3 Perkins, Charles B. 3 Wang, J. Christina 3 Webel, Karsten 3 Agatz, Niels 2 Bremer, Leon 2 Dionne, Georges 2 Greyling, Talita 2 Hagen, Liana van der 2 Hajiyev, Murad 2 Kis-Katos, Krisztina 2 Kneib, Thomas 2 Lenel, Friederike 2 Lu, Yao 2 Muth, Manuel 2 Nufer, Gerd 2 Nölting, Christopher 2 Poutré, Cédric 2 Rossouw, Stephanié 2 Spliet, Remy 2 Visser, Thomas R. 2 Weisser, Christoph 2 Yergeau, Gabriel 2 Aagaard, Harriet 1 Batouche, Mohamed 1 Baumann, Philipp 1 Beckel, Christian 1 Boomgaarden, Hajo G. 1 Boucheham, Anouar 1 Castro, Daniel Tavares de 1 Chai, Yidong 1 Chandramouliswaran S 1 Chen, Xi 1 Choi, Chang Won 1 David, Esther 1 Delden, Arnout van 1 Ding, Hao 1
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Published in...
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Computational economics 2 Discussion paper series 2 European journal of operational research : EJOR 2 IZA Discussion Papers 2 Journal of management information systems : JMIS 2 The Review of International Organizations 2 African journal of science, technology, innovation and development : AJSTID 1 CIRRELT 1 CPB discussion paper 1 Computational Communication Research 1 Data science and management : DSM 1 Deutsche Bundesbank Discussion Paper 1 Development Engineering 1 Development engineering 1 Discussion paper 1 Discussion paper / Central Bureau voor de Statistiek 1 Discussion paper / Tinbergen Institute 1 Discussion papers / CEPR 1 ERIM report series research in management 1 Energy 1 GLO Discussion Paper 1 GLO discussion paper 1 Global Cooperation Research Papers 1 Global cooperation research papers 1 IMF working papers 1 INFORMS journal on computing : JOC 1 ISER Working Paper Series 1 ISER working paper series 1 Intelligent systems in accounting, finance & management 1 International Journal of Applied Metaheuristic Computing (IJAMC) 1 International Journal of Information Systems for Crisis Response and Management (IJISCRAM) 1 International journal of market research : JMRS ; the journal of the Market Research Society 1 International marketing review 1 International review of financial analysis 1 Journal of Documentation 1 Journal of behavioral and experimental finance 1 Journal of business analytics 1 Journal of business research : JBR 1 Journal of econometric methods 1 Journal of health economics 1
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Source
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ECONIS (ZBW) 46 EconStor 14 Other ZBW resources 4 RePEc 1
Showing 41 - 50 of 65
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A random forest-based approach to identifying the most informative seasonality tests
Ollech, Daniel; Webel, Karsten - 2020
Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...
Persistent link: https://www.econbiz.de/10012301212
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A random forest-based approach to identifying the most informative seasonality tests
Ollech, Daniel; Webel, Karsten - 2020
Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...
Persistent link: https://www.econbiz.de/10012302182
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International high-frequency arbitrage for cross-listed stocks
Poutré, Cédric; Dionne, Georges; Yergeau, Gabriel - In: International review of financial analysis 89 (2023), pp. 1-18
Persistent link: https://www.econbiz.de/10014467063
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Predicting tax fraud using supervised machine learning approach
Murorunkwere, Belle Fille; Haughton, Dominique; … - In: African journal of science, technology, innovation and … 15 (2023) 6, pp. 731-742
Persistent link: https://www.econbiz.de/10014391945
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An ensemble-based machine learning model for emotion and mental health detection
Jonnalagadda, Annapurna; Rajvir, Manan; Singh, Shovan; … - In: Journal of information & knowledge management : JIKM 22 (2023) 2, pp. 1-24
Persistent link: https://www.econbiz.de/10014387881
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Brand anthropomorphism on Twitter : communication strategies and consumer engagement
Wu, Linwan; Dodoo, Naa Amponsah; Choi, Chang Won - In: The journal of product & brand management 32 (2023) 6, pp. 799-811
Persistent link: https://www.econbiz.de/10014315448
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When injured product users may also stay satisfied : a macro-level analysis
Vaid, Shashank; Donthu, Naveen - In: Journal of business research : JBR 162 (2023), pp. 1-13
Persistent link: https://www.econbiz.de/10014302555
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A random forest-based approach to combining and ranking seasonality tests
Ollech, Daniel; Webel, Karsten - In: Journal of econometric methods 12 (2023) 1, pp. 117-130
Persistent link: https://www.econbiz.de/10013554738
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How magic a bullet is machine learning for credit analysis? : an exploration with FinTech lending data
Wang, J. Christina; Perkins, Charles B. - 2019 - This version: October 2019
FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...
Persistent link: https://www.econbiz.de/10012135725
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Machine learning and causality : the impact of financial crises on growth
Tiffin, Andrew - 2019
Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some...
Persistent link: https://www.econbiz.de/10012154563
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