Systematic Review of Using Machine Learning in Imputing Missing Values

Systematic Review of Using Machine Learning in Imputing Missing Values

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Missing data are a universal data quality problem in many domains, leading to misleading analysis and inaccurate decisions. Much research has been done to investigate the different mechanisms of missing data and the proper techniques in handling various data types. In the last decade, machine learni...

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Bibliographic Details
Main Authors: Mustafa Alabadla, Fatimah Sidi, Iskandar Ishak, Hamidah Ibrahim, Lilly Suriani Affendey, Zafienas Che Ani, Marzanah A. Jabar, Umar Ali Bukar, Navin Kumar Devaraj, Ahmad Sobri Muda, Anas Tharek, Noritah Omar, M. Izham Mohd Jaya
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Systematic literature review
data imputation
data mining
missingness
data preprocessing
data quality
Online Access:https://ieeexplore.ieee.org/document/9762231/

Internet

https://ieeexplore.ieee.org/document/9762231/

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