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Applied Economics Letters Volume 28, 2021 - Issue 1
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Research Article

An AutoML application to forecasting bank failures

Anna Agrapetidoua Department of Economics, Democritus University of Thrace, Komotini, GreeceCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-8407-7552
ORCID Icon,
Paulos Charonyktakisb Gnosis Data Analysis PC, Heraklion, Greece
,
Periklis Gogasa Department of Economics, Democritus University of Thrace, Komotini, Greece
,
Theophilos Papadimitrioua Department of Economics, Democritus University of Thrace, Komotini, Greece
&
Ioannis Tsamardinosb Gnosis Data Analysis PC, Heraklion, Greece;c Computer Science Department, University of Crete, Heraklion, Greece
Pages 5-9 | Published online: 03 Feb 2020

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Yuda N. Mnyawami, Hellen H. Maziku & Joseph C. Mushi. (2022) Enhanced Model for Predicting Student Dropouts in Developing Countries Using Automated Machine Learning Approach: A Case of Tanzanian’s Secondary Schools. Applied Artificial Intelligence 36:1.
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Vivek Kumar Singh & Kailash Joshi. (2022) Automated Machine Learning (AutoML): an overview of opportunities for application and research. Journal of Information Technology Case and Application Research 24:2, pages 75-85.
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Ioannis Tsamardinos, Paulos Charonyktakis, Georgios Papoutsoglou, Giorgos Borboudakis, Kleanthi Lakiotaki, Jean Claude Zenklusen, Hartmut Juhl, Ekaterini Chatzaki & Vincenzo Lagani. (2022) Just Add Data: automated predictive modeling for knowledge discovery and feature selection. npj Precision Oncology 6:1.
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Oded Koren, Carina A. Hallin, Michal Koren & Amir A. Issa. (2021) AutoML classifier clustering procedure. International Journal of Intelligent Systems 37:7, pages 4214-4232.
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Vasco Lopes, Antonio Gaspar, Luis A. Alexandre & Joao Cordeiro. (2021) An AutoML-based Approach to Multimodal Image Sentiment Analysis. An AutoML-based Approach to Multimodal Image Sentiment Analysis.
S. V. Palmov. (2020) Studying the capabilities of the analytical system based on the machine learning method. Radio industry (Russia) 30:3, pages 112-126.
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Karen-Inge Karstoft, Ioannis Tsamardinos, Kasper Eskelund, Søren Bo Andersen & Lars Ravnborg Nissen. (2020) Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning. JMIR Medical Informatics 8:7, pages e17119.
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