Impact of Missing Data on Classification Success in Health and Comparative Analysis of Imputation Methods-Reference-Cited by-同舟云学术

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Impact of Missing Data on Classification Success in Health and Comparative Analysis of Imputation Methods

Published:2022-07-19 Issue: Volume: Page:
ISSN:
Container-title:2022 International Symposium on Networks, Computers and Communications (ISNCC)
language:
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Author:

Ergun Ebru Ucgun¹,Kok Ibrahim²,Ozdemir Suat³

Affiliation:

1. Defense Systems Technologies ASELSAN,Ankara,Turkey

2. Pamukkale University,Department of Computer Engineering,Denizli,Turkey

3. Hacettepe University,Department of Computer Engineering,Ankara,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9851698/9851699/09851791.pdf?arnumber=9851791

Reference30 articles.

1. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance

2. AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity

3. Multi-Attribute Missing Data Reconstruction Based on Adaptive Weighted Nuclear Norm Minimization in IoT

4. Handling missing data in large healthcare dataset: A case study of unknown trauma outcomes

5. Probabilistic Recovery of Incomplete Sensed Data in IoT

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explainable AI-Based Malicious Traffic Detection and Monitoring System in Next-Gen IoT Healthcare;2023 International Conference on Smart Applications, Communications and Networking (SmartNets);2023-07-25

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