Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis

Citations

Cited by:

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7. Mahmoud Abdel-Sattar & Adel M. Al-Saif & Abdulwahed M. Aboukarima & Dalia H. Eshra & Lidia Sas-Paszt, 2022. "Quality Attributes Prediction of Flame Seedless Grape Clusters Based on Nutritional Status Employing Multiple Linear Regression Technique," Agriculture, MDPI, vol. 12(9), pages 1-19, August.
8. Smeele, Nicholas V.R. & Chorus, Caspar G. & Schermer, Maartje H.N. & de Bekker-Grob, Esther W., 2023. "Towards machine learning for moral choice analysis in health economics: A literature review and research agenda," Social Science & Medicine, Elsevier, vol. 326(C).
9. Horvath, Sabine & Soot, Matthias & Zaddach, Sebastian & Neuner, Hans & Weitkamp, Alexandra, 2021. "Deriving adequate sample sizes for ANN-based modelling of real estate valuation tasks by complexity analysis," Land Use Policy, Elsevier, vol. 107(C).
10. Sophia Voulgaropoulou & Nikolaos Samaras & Nikolaos Ploskas, 2022. "Predicting the Execution Time of the Primal and Dual Simplex Algorithms Using Artificial Neural Networks," Mathematics, MDPI, vol. 10(7), pages 1-21, March.
11. Coqueret, Guillaume & Deguest, Romain, 2024. "Unexpected opportunities in misspecified predictive regressions," European Journal of Operational Research, Elsevier, vol. 318(2), pages 686-700.
12. Wang, Yuanping & Hou, Lingchun & Hu, Lang & Cai, Weiguang & Wang, Lin & Dai, Cuilian & Chen, Juntao, 2023. "How family structure type affects household energy consumption: A heterogeneous study based on Chinese household evidence," Energy, Elsevier, vol. 284(C).
13. Oguzhan Essiz & Aysu Senyuz, 2024. "Predicting the value‐based determinants of sustainable luxury consumption: A multi‐analytical approach and pathway to sustainable development in the luxury industry," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 1721-1758, March.
14. Guillaume Coqueret & Romain Deguest, 2024. "Unexpected opportunities in misspecified predictive regressions," Post-Print hal-04595355, HAL.
15. Shu-Long Luo & Xing Shi & Feng Yang, 2024. "A Review of Data-Driven Methods in Building Retrofit and Performance Optimization: From the Perspective of Carbon Emission Reductions," Energies, MDPI, vol. 17(18), pages 1-33, September.
16. Mihai Mutascu & Scott W. Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 400-416, June.
    • Mihai Mutascu & Scott Hegerty, 2023. "Predicting the contribution of artificial intelligence to unemployment rates: an artificial neural network approach," Post-Print hal-04273887, HAL.
17. Ester Vasta & Tommaso Scimone & Giovanni Nobile & Otto Eberhardt & Daniele Dugo & Massimiliano Maurizio De Benedetti & Luigi Lanuzza & Giuseppe Scarcella & Luca Patanè & Paolo Arena & Mario Cacciato, 2023. "Models for Battery Health Assessment: A Comparative Evaluation," Energies, MDPI, vol. 16(2), pages 1-34, January.
18. Alwosheel, Ahmad & van Cranenburgh, Sander & Chorus, Caspar G., 2019. "‘Computer says no’ is not enough: Using prototypical examples to diagnose artificial neural networks for discrete choice analysis," Journal of choice modelling, Elsevier, vol. 33(C).
19. Sadia Samar Ali & Rajbir Kaur & D. Jinil Persis & Raiswa Saha & Murugan Pattusamy & V. Raja Sreedharan, 2023. "Developing a hybrid evaluation approach for the low carbon performance on sustainable manufacturing environment," Annals of Operations Research, Springer, vol. 324(1), pages 249-281, May.
20. Ibrahim A. Nafisah & Irsa Sajjad & Mohammed A. Alshahrani & Osama Abdulaziz Alamri & Mohammed M. A. Almazah & Javid Gani Dar, 2024. "Statistical Predictive Hybrid Choice Modeling: Exploring Embedded Neural Architecture," Mathematics, MDPI, vol. 12(19), pages 1-20, October.
21. Melvin Wong & Bilal Farooq, 2019. "ResLogit: A residual neural network logit model for data-driven choice modelling," Papers 1912.10058, arXiv.org, revised Feb 2021.
22. Salah Alghamdi & Waiching Tang & Sittimont Kanjanabootra & Dariusz Alterman, 2024. "Optimising Building Energy and Comfort Predictions with Intelligent Computational Model," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
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27. Shuangyang Lai & Haoming Chen & Yuexu Zhao, 2024. "Measurement and prediction of the development level of China’s digital economy," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.