Usage of Nearest Neighborhood, Decision Tree and Bayesian Classification Techniques in Development of Weight Management Counseling System

Abstract

Case based reasoning (CBR) is an approach for solving a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. Selection and generation of cases are two important components of a CBR system. Obesity is one of the most significant public health problems facing the whole world. Children have been weighing progressively more since the 1970s, the first phase of the obesity epidemic that now has entered a second phase of serious health problems related to overweight, including diabetes, certain types of cancer, and cardiovascular disease. Proper counseling on nutrition and appropriate physical activity can control the problem of obesity. In previous paper, we proposed a case based framework for weight management counseling to obese children. In this paper, three data mining techniques: nearest neighborhood, decision tree and Bayesian classification, were applied on distributed case bases for case retrieval and case adaptation.