COVID-19 Data Analysis: The Impact of Missing Data Imputation on Supervised Learning Model Performance
The global COVID-19 pandemic has generated extensive datasets, providing opportunities to apply machine learning for diagnostic purposes. This study evaluates the performance of five supervised learning models—Random Forests (RFs), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), L...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/13/3/70 |
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