AbstractThis research aims to develop an imputation framework for the National Childhood
Development Research Centre (NCDRC)’s missing data. Missing data and other associated
issues, such as outliers, time points, noise, and continuity, were the main challenges in this
research. The nature of the NCDRC dataset was not consistent with those reported in the
literature, with the latter being more randomly scattered and copious and having no
patterns, making it difficult to find and select relevant experimental data. The
VIseKriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was utilized to select the
best continuous portion of Body Mass Index (BMI) data over 182 different portions, which
accounted for 911 participants (i.e. children with complete records) over seven (7) continuous
time points. Three different machine learning algorithms to im.....