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Machine learning algorithm validation with a limited sample size

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Cited by:

  1. Shravankumar Shivappa Masalvad & Chidanand Patil & Akkaram Pravalika & Basavaraj Katageri & Purandara Bekal & Prashant Patil & Nagraj Hegde & Uttam Kumar Sahoo & Praveen Kumar Sakare, 2024. "Application of geospatial technology for the land use/land cover change assessment and future change predictions using CA Markov chain model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 24817-24842, October.
  2. Qiaoyang Li & Guiming Chen, 2021. "Recognition of industrial machine parts based on transfer learning with convolutional neural network," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-21, January.
  3. Li-Dunn Chen & Michael A Caprio & Devin M Chen & Andrew J Kouba & Carrie K Kouba, 2024. "Enhancing predictive performance for spectroscopic studies in wildlife science through a multi-model approach: A case study for species classification of live amphibians," PLOS Computational Biology, Public Library of Science, vol. 20(2), pages 1-24, February.
  4. Bhattacharjee, Biplab & Kumar, Rajiv & Senthilkumar, Arunachalam, 2022. "Unidirectional and bidirectional LSTM models for edge weight predictions in dynamic cross-market equity networks," International Review of Financial Analysis, Elsevier, vol. 84(C).
  5. Mahdi Goldani & Soraya Asadi Tirvan, 2024. "Sensitivity Assessing to Data Volume for forecasting: introducing similarity methods as a suitable one in Feature selection methods," Papers 2406.04390, arXiv.org.
  6. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
  7. Sinha, Shruti & Sankar Rao, Chinta & Kumar, Abhishankar & Venkata Surya, Dadi & Basak, Tanmay, 2024. "Exploring and understanding the microwave-assisted pyrolysis of waste lignocellulose biomass using gradient boosting regression machine learning model," Renewable Energy, Elsevier, vol. 231(C).
  8. Sihyun An & Yena Song & Hanwool Jang & Kwangwon Ahn, 2025. "Toward transparent and accurate housing price appraisal: Hedonic price models versus machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-29, December.
  9. Giannakeas, Ilias N. & Mazaheri, Fatemeh & Bacarreza, Omar & Khodaei, Zahra Sharif & Aliabadi, Ferri M.H., 2023. "Probabilistic residual strength assessment of smart composite aircraft panels using guided waves," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  10. Muhammad Nabihan Abu Bakar & Muhammad Hakimi Tew Abdullah & Masliya Yahya & Fakrulnizam Jafri & Amirah Hassan @ Asan, 2026. "Drivers of Online Impulse Buying Behaviour: The Effects of Social Media Promotion and Peer Interaction Among UiTM Rembau Undergraduates," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 10(5), pages 2597-2611, May.
  11. Min Yang & Baiyu Zhang & Yifu Chen & Xiaying Xin & Kenneth Lee & Bing Chen, 2021. "Impact of Microplastics on Oil Dispersion Efficiency in the Marine Environment," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
  12. Twumasi, Clement & Twumasi, Juliet, 2022. "Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1258-1277.
  13. Dell’Anna, Federico, 2025. "Machine learning framework for evaluating energy performance certificate (EPC) effectiveness in real estate: A case study of Turin’s private residential market," Energy Policy, Elsevier, vol. 198(C).
  14. Muhammad Tanveer Islam & Sartaj Aziz Turja & Md Tawfiqul Islam & Md Mominur Rahman & Ahsan Habib, 2025. "Forecasting Tetouan energy demand employing shift approach in machine-learning: complementing econometric insights," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1833-1860, April.
  15. Stephan Breimann & Frits Kamp & Gabriele Basset & Claudia Abou-Ajram & Gökhan Güner & Kanta Yanagida & Masayasu Okochi & Stephan A. Müller & Stefan F. Lichtenthaler & Dieter Langosch & Dmitrij Frishma, 2025. "Charting γ-secretase substrates by explainable AI," Nature Communications, Nature, vol. 16(1), pages 1-20, December.
  16. Reza Rezaee & Jamiu Ekundayo, 2022. "Permeability Prediction Using Machine Learning Methods for the CO 2 Injectivity of the Precipice Sandstone in Surat Basin, Australia," Energies, MDPI, vol. 15(6), pages 1-15, March.
  17. Nica-Avram, Georgiana & Harvey, John & Smith, Gavin & Smith, Andrew & Goulding, James, 2021. "Identifying food insecurity in food sharing networks via machine learning," Journal of Business Research, Elsevier, vol. 131(C), pages 469-484.
  18. Leandro C. Hermida & E. Michael Gertz & Eytan Ruppin, 2022. "RETRACTED ARTICLE: Predicting cancer prognosis and drug response from the tumor microbiome," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  19. Jonathan C. M. Wan & Dennis Stephens & Lingqi Luo & James R. White & Caitlin M. Stewart & Benoît Rousseau & Dana W. Y. Tsui & Luis A. Diaz, 2022. "Genome-wide mutational signatures in low-coverage whole genome sequencing of cell-free DNA," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  20. Bhattarai, Bishwoyog & Leasor, Zachary & Reis, André Fróes de Borja, 2025. "Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S," Agricultural Water Management, Elsevier, vol. 319(C).
  21. Michael D. Wang & Jie Lou & Dong Zhang & C. Simon Fan, 2022. "Measuring political and economic uncertainty: a supervised computational linguistic approach," SN Business & Economics, Springer, vol. 2(5), pages 1-17, May.
  22. Steffen Steinert & Verena Ruf & David Dzsotjan & Nicolas Großmann & Albrecht Schmidt & Jochen Kuhn & Stefan Küchemann, 2024. "A refined approach for evaluating small datasets via binary classification using machine learning," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-21, May.
  23. Nelson Kimeli Kemboi Yego & Joseph Nkurunziza & Juma Kasozi, 2023. "Predicting health insurance uptake in Kenya using Random Forest: An analysis of socio-economic and demographic factors," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-19, November.
  24. Alexis H. Villacis & Syed Badruddoza & Ashok K. Mishra, 2024. "A machine learning‐based exploration of resilience and food security," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(4), pages 1479-1505, December.
  25. Gregory Hoy & Thomas Cortier & Hannah E. Maier & Guillermina Kuan & Roger Lopez & Nery Sanchez & Sergio Ojeda & Miguel Plazaola & Daniel Stadlbauer & Abigail Shotwell & Angel Balmaseda & Florian Kramm, 2025. "Anti-neuraminidase and anti-HA stalk antibodies reduce the susceptibility to and infectivity of influenza A/H3N2 virus," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
  26. Xiaofeng Xu & Zhaoyuan Chen & Shixiang Chen, 2023. "Enhancing economic competitiveness analysis through machine learning: Exploring complex urban features," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-27, November.
  27. Ciaran Michael Kelly & Russell Lewis McLaughlin, 2024. "Comparison of machine learning methods for genomic prediction of selected Arabidopsis thaliana traits," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-13, August.
  28. Alexander Rokoss & Marius Syberg & Laura Tomidei & Christian Hülsing & Jochen Deuse & Matthias Schmidt, 2024. "Case study on delivery time determination using a machine learning approach in small batch production companies," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3937-3958, December.
  29. Kristof Lommers & Ouns El Harzli & Jack Kim, 2021. "Confronting Machine Learning With Financial Research," Papers 2103.00366, arXiv.org, revised Mar 2021.
  30. Qianru Qi & Rongjun Cheng & Hongxia Ge, 2022. "Short-Term Travel Demand Prediction of Online Ride-Hailing Based on Multi-Factor GRU Model," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
  31. Jiayu Sun & Vincenzina Caputo & Hannah Taylor, 2024. "Using machine‐learning methods in meta‐analyses: An empirical application on consumer acceptance of meat alternatives," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(4), pages 1506-1532, December.
  32. Daniel Niguse Mamo & Agmasie Damtew Walle & Eden Ketema Woldekidan & Jibril Bashir Adem & Yosef Haile Gebremariam & Meron Asmamaw Alemayehu & Ermias Bekele Enyew & Shimels Derso Kebede, 2025. "Performance evaluation and comparative analysis of different machine learning algorithms in predicting postnatal care utilization: Evidence from the ethiopian demographic and health survey 2016," PLOS Digital Health, Public Library of Science, vol. 4(1), pages 1-25, January.
  33. Francisco Gatica-Neira & Mario Ramos-Maldonado, 2022. "Limits to the Productivity in Biobased Territorial SMEs," SAGE Open, , vol. 12(2), pages 21582440221, May.
  34. Carlo Dindorf & Eva Bartaguiz & Freya Gassmann & Michael Fröhlich, 2022. "Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review," IJERPH, MDPI, vol. 20(1), pages 1-23, December.
  35. Bruttel, Lisa & Nithammer, Juri, 2025. "Opinion Piece: How to pre-register experimental studies that involve machine learning for text data analysis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 118(C).
  36. Zhou, Huanyu & Qiu, Yingning & Feng, Yanhui & Liu, Jing, 2022. "Power prediction of wind turbine in the wake using hybrid physical process and machine learning models," Renewable Energy, Elsevier, vol. 198(C), pages 568-586.
  37. Jacob Beck, 2023. "Quality aspects of annotated data," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 17(3), pages 331-353, December.
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