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首页> 外文会议>2019 10th International Conference on Dependable Systems, Services and Technologies >A Machine Learning Approach for Predicting Weight Gain Risks in Young Adults
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A Machine Learning Approach for Predicting Weight Gain Risks in Young Adults

机译：一种预测年轻人体重增加风险的机器学习方法

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Individuals developing signs of weight gain or obesity are at a risk of developing serious illnesses such as type 2 diabetes, respiratory problems, coronary heart disease and stroke. Physical activity and healthy eating can be a fundamental component to maintain a healthy lifestyle. Therefore, detecting childhood obesity is of paramount importance. This paper utilises the vast amount of data available via the millennium cohort study. Various regression methods and artificial neural network models have been evaluated to predict the teenager BMI from earlier BMI values. The results obtained are encouraging and a prediction accuracy of over 90% has been achieved. Various issues relating to data mining and prediction accuracy are discussed.
机译：出现体重增加或肥胖迹象的个体有发展为2型糖尿病，呼吸系统疾病，冠心病和中风等严重疾病的风险。体育锻炼和健康饮食可以成为维持健康生活方式的基本要素。因此，检测儿童肥胖至关重要。本文利用了通过千年队列研究获得的大量数据。已评估了各种回归方法和人工神经网络模型，以根据较早的BMI值预测青少年BMI。获得的结果令人鼓舞，并且已达到90％以上的预测精度。讨论了与数据挖掘和预测准确性有关的各种问题。

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