What is Classification Accuracy

Individuals with intellectual disabilities (ID) have considerable health inequalities including higher levels of unmet health needs and a shorter life expectancy compared to the general population. The prevalence of obesity, a commonly accepted measure of health inequalities, is higher in people with ID than in the general population, and the factors leading to the increased prevalence among people with ID have not been well understood yet. This has become worse during the COVID-19 pandemic due to nationwide full and partial curfews. In this study, based on a dataset that comprises a set of parameters related to eating habits and physical conditions of a number individuals, the use of classification algorithms for predicting obesity levels of individuals with ID is proposed, and a performance analysis is made using well-known performance metrics. The results could be used by researchers and practitioners in this field to choose the best classifier for their mobile application solutions. Opportunities, research challenges, and future research directions in this topic are also presented.