Machine Learning Algorithms in Identifying Balanced Diet Plan for Healthy Life style

Abstract

The present generation of all ages is terribly facing the challenges of obesity in recent times. The people suffering from this disorder practice different diet plans for weight reduction without considering the balanced proportion of nutrients in their diet. This paper aims in highlighting the ill effects of unbalanced diet plans and proposes a machine learning (ML) model based on support vector machine to make decisions on the balanced nature of the diet. The efficiency of the proposed ML model is compared with other ML algorithms. The accuracy results of the proposed model are more convincing in comparison with other ML algorithms. The proposed ML model is applied to deterministic type of secondary data sets and this shall be extended by applying to fuzzy data sets. This research work applies the algorithms of machine learning to health-based decision-making systems