Mixed Data Imputation Using Generative Adversarial Networks

Mixed Data Imputation Using Generative Adversarial Networks

Missing values are common in real-world datasets and pose a significant challenge to the performance of statistical and machine learning models. Generally, missing values are imputed using statistical methods, such as the mean, median, mode, or machine learning approaches. These approaches are limit...

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Bibliographic Details
Main Authors: Wasif Khan, Nazar Zaki, Amir Ahmad, Mohammad Mehedy Masud, Luqman Ali, Nasloon Ali, Luai A. Ahmed
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Mixed data imputation
missing data
GANs
miss forest
MICE
denoising auto encoders
Online Access:https://ieeexplore.ieee.org/document/9932604/

Internet

https://ieeexplore.ieee.org/document/9932604/

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