Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method (NNM) and Expectation-Maximization (EM) Algorithm

Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method (NNM) and Expectation-Maximization (EM) Algorithm

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Missing data in large data analysis has affected further analysis conducted on dataset. To fill in missing data, Nearest Neighbour Method (NNM) and Expectation Maximization (EM) algorithm are the two most widely used methods. Thus, this research aims to compare both methods by imputing missing data...

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Bibliographic Details
Main Authors: Muhammad Izzuddin Rumaling, Fuei Pien Chee, Jedol Dayou, Jackson Hian Wui Chang, Steven Soon Kai Kong, Justin Sentian
Format: Article
Language:English
Published: Springer 2020-03-01
Series:Asian Journal of Atmospheric Environment
Subjects:
particulate matter
missing data
nearest neighbour method
expectation maximization algorithm
performance indicators
Online Access:http://www.asianjae.org/_common/do.php?a=full&b=11&bidx=1922&aidx=23538

Internet

http://www.asianjae.org/_common/do.php?a=full&b=11&bidx=1922&aidx=23538

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