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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. 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.
  5. 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).
  6. 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.
  7. 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.
  8. 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).
  9. 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.
  10. 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).
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. Kristof Lommers & Ouns El Harzli & Jack Kim, 2021. "Confronting Machine Learning With Financial Research," Papers 2103.00366, arXiv.org, revised Mar 2021.
  17. 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.
  18. 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.
  19. Francisco Gatica-Neira & Mario Ramos-Maldonado, 2022. "Limits to the Productivity in Biobased Territorial SMEs," SAGE Open, , vol. 12(2), pages 21582440221, May.
  20. 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.
  21. 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.
  22. 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.
  23. Leandro C. Hermida & E. Michael Gertz & Eytan Ruppin, 2022. "Predicting cancer prognosis and drug response from the tumor microbiome," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  24. 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.
  25. 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.
  26. 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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