Cyclical hybrid imputation technique for missing values in data sets
Abstract The problem of missing data in data sets is the most important first step to be addressed in the preprocessing phase. Because incorrect imputation of missing data increases the error in the modeling phase and reduces the prediction performance of the model. When it comes to health, it is in...
| Автори: | , |
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| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Nature Portfolio
2025-02-01
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| Серія: | Scientific Reports |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1038/s41598-025-90964-7 |