A systematic review of recurrent neural network adoption in missing data imputation
Missing data is a pervasive challenge in diverse datasets accross various domains. It is often resulting from human error, system faults, and respondent non-response. Failing to address missing data can lead to inaccurate results during data analysis, as incomplete data sequences introduce biases an...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
University of Bahrain
2025
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/43919/1/1571041166.pdf http://umpir.ump.edu.my/id/eprint/43919/ http://dx.doi.org/10.12785/ijcds/1571041166 |
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