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

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 of air quality in five monitoring stations (CA0030, CA0039, CA0042, CA0049, CA0050) in Sabah, Malaysia. PM10 (particulate matter with aerodynamic size below 10 microns) dataset in the range from 2003-2007 (Part A) and 2008-2012 (Part B) are used in this research. To make performance evaluation possi... Mehr ...