Alimentation Status Classification System Using KNN and Naive Bayesian Classifiers

Abstract

Nowadays, there is an increasing interest about child health care in the developing countries. Because the future of each country is based on many youths, they need to be healthy. So, it is needed to takecare the health of each child since childhood. Good alimentation is prime important in the attainment of normal growth and development, and in the maintenance of health throughout life. Especially in their earlier live, the children need adequate quantity and appropriate quality of food to meet the alimentation requirement for their physical, mental growth and development. So, this system is proposed as the alimentation status classification system for children. This system classifies the child who has alimentation status or mal-alimentation by using k-nearest neighbor (KNN) and naive bayesian classifiers. Moreover, this system compares the performance of these two classifiers to know which classifier is more precise than other for child’s alimentation status classification.