Investigation of Nutritional Status of Children based on Machine Learning Techniques using Indian Demographic and Health Survey Data

Abstract

Malnutrition is the leading causes of infant mortality among the developing countries including India. This study designs a prediction model for malnutrition based on machine learning approach, using the available features in the Indian Demographic and Health Survey (IDHS) dataset and comparing that with the literature identified features. Our findings suggest that machine learning approach identifies some important features not identified in extant literature. Subsequently, logistic regression was carried out to identify the probabilities of these features in explaining malnutrition. The paper contributes in exploring the possibilities of using artificial intelligence in identifying probable correlates of malnutrition.