Application of machine learning based algorithm for prediction of malnutrition among women in Bangladesh

Malnutrition among women is a major public health problem that has been linked to stunted growth, diabetes, and has adverse consequences for children, including low birth weight, less resistance to infections, and a higher risk of death. This current study presents an exhaustive comprehensive study of machine learning (ML) system which has two major objectives: (i) identification of the potential risk factors of malnourished women; and (ii) propose a better ML-based model for predicting malnourished women. About 15,464 respondents were taken from the Bangladesh Demographic and Health Survey. The potential risk factors for malnutrition were extracted using multinomial logistic regression (MLR). Five ML-based algorithms such as Naïve Bayes, support vector machine, decision tree, artificial neural network, and random forest (RF)…