PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Journal of Health Informatics and Statistics10.21032/jhis.2022.47.3.2172022473217-221Performance Comparison of Imputation Methods Using Machine Learning Techniques for Ordinal Missing DataSerhim Son, Hyonggin Anhttp://e-jhis.org/upload/pdf/jhis-47-3-217.pdf, http://e-jhis.org/journal/view.php?doi=10.21032/jhis.2022.47.3.217, http://e-jhis.org/upload/pdf/jhis-47-3-217.pdf
2020 28th Signal Processing and Communications Applications Conference (SIU)10.1109/siu49456.2020.93022222020Missing data imputation using machine learning based methods to improve HCC survival predictionMehmethan Yumus, Merve Apaydin, Ali Degirmenci, Omer Karalhttp://xplorestaging.ieee.org/ielx7/9302025/9302026/09302222.pdf?arnumber=9302222
Intelligent Computing10.1007/978-3-030-22871-2_512019738-750Performance Analysis of Missing Values Imputation Methods Using Machine Learning TechniquesOmesaad Rado, Muna Al Fanah, Ebtesam Taktekhttp://link.springer.com/content/pdf/10.1007/978-3-030-22871-2_51
Machine Learning and Knowledge Extraction10.3390/make4040041202244827-838Comparison of Imputation Methods for Missing Rate of Perceived Exertion Data in RugbyAmarah Epp-Stobbe, Ming-Chang Tsai, Marc Klimstrahttps://www.mdpi.com/2504-4990/4/4/41/pdf
Soft Computing10.1007/s00500-019-04199-620192464361-4392Missing value imputation using unsupervised machine learning techniquesP. S. Raja, K. Thangavelhttp://link.springer.com/content/pdf/10.1007/s00500-019-04199-6.pdf, http://link.springer.com/article/10.1007/s00500-019-04199-6/fulltext.html, http://link.springer.com/content/pdf/10.1007/s00500-019-04199-6.pdf
Data Technologies and Applications10.1108/dta-12-2020-02982021554558-585A systematic review of machine learning-based missing value imputation techniquesTressy Thomas, Enayat Rajabihttps://www.emerald.com/insight/content/doi/10.1108/DTA-12-2020-0298/full/xml, https://www.emerald.com/insight/content/doi/10.1108/DTA-12-2020-0298/full/html
10.26434/chemrxiv.131249932021Imputation of Missing Gas Permeability Data for Polymer Membranes using Machine LearningQi Yuan, Mariagiulia Longo, Aaron Thornton, Neil B. McKeown, Bibiana Comesana-Gandara, Johannes C. Jansen, Kim Jelfshttps://ndownloader.figshare.com/files/26436020
Scientific Reports10.1038/s41598-023-36509-22023131A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methodsYingfeng Ge, Zhiwei Li, Jinxin Zhanghttps://www.nature.com/articles/s41598-023-36509-2.pdf, https://www.nature.com/articles/s41598-023-36509-2, https://www.nature.com/articles/s41598-023-36509-2.pdf
10.26434/chemrxiv.13124993.v22021Imputation of Missing Gas Permeability Data for Polymer Membranes using Machine LearningQi Yuan, Mariagiulia Longo, Aaron Thornton, Neil B. McKeown, Bibiana Comesana-Gandara, Johannes C. Jansen, Kim Jelfshttps://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/60c75533bdbb899471a3a7aa/original/imputation-of-missing-gas-permeability-data-for-polymer-membranes-using-machine-learning.pdf
10.26434/chemrxiv.13124993.v12020Imputation of Missing Gas Permeability Data for Polymer Membranes using Machine LearningQi Yuan, Mariagiulia Longo, Aaron Thornton, Neil B. McKeown, Bibiana Comesana-Gandara, Johannes C. Jansen, Kim Jelfshttps://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/60c754f2bb8c1a7b1d3dc329/original/imputation-of-missing-gas-permeability-data-for-polymer-membranes-using-machine-learning.pdf