确定健康生活方式均衡饮食计划的机器学习算法

M. Nivetha, P. Pandiammal, Gandhi Ramila
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引用次数: 0

摘要

当今时代,所有年龄段的人都面临着肥胖的挑战。患有这种疾病的人采用不同的饮食计划来减肥,而不考虑饮食中营养成分的平衡比例。本文旨在突出不平衡饮食计划的不良影响,并提出了一种基于支持向量机的机器学习(ML)模型来对饮食的平衡性质进行决策。将该模型的效率与其他机器学习算法进行了比较。与其他机器学习算法相比,该模型的准确率结果更具说服力。提出的机器学习模型适用于确定性类型的辅助数据集,并将其扩展到模糊数据集。本研究工作将机器学习算法应用于基于健康的决策系统
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Algorithms in Identifying Balanced Diet Plan for Healthy Life style
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
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