Single and multiple imputation method to replace missing values in air pollution datasets: A review

Single and multiple imputation method to replace missing values in air pollution datasets: A review

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Imputation plays an essential role in handling the issue of missing data. The conventional techniques applied to overcome this problem are single imputation (SI) and multiple imputations (MI). These statistical strategies have their strengths and limitations in replacing missing data. This article r...

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Bibliographic Details
Main Authors: Ahmat, H. (Author), Amat R.C (Author), Ibrahim N.M (Author), Izhar T.N.T (Author), Libasin, Z. (Author), Noor N.M (Author), Rahim N.L (Author), Shaziayani, W.N (Author), Ting S.S (Author), Ul-Saufie, A.Z (Author), Yusof S.Y (Author), Zakarya I.A (Author)
Format: Article
Language:English
Published: IOP Publishing Ltd, 2020
Subjects:
Air pollution
Conventional techniques
Environmental technology
Imputation methods
Imputation techniques
Machine learning
Machine learning approaches
Multiple imputation
Single imputation
State of the art
Statistical strategies
Turing machines
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