Indication of Health Status Using Machine Learning Linear Regression and Random Forest

被引:0
|
作者
Asif, Arslan [1 ]
Nabeel, Muhammad [1 ]
Awan, Mazhar Javed [1 ]
Ahsan, Muhammad [1 ]
Hannan, Abdul [1 ]
Abbas, Shahroz [1 ]
机构
[1] Univ Management & Technol, Dept Software Engn, Lahore, Pakistan
关键词
Machine Learning; BMI; Prediction of Health; Health Status by BMI; Obesity Level; PREDICTION;
D O I
10.1109/ICIC53490.2021.9693018
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In today's modern world obesity has become a major problem and everyone wants to get fit. Hence, to decide on a proper diet plan and health status we need BMI (Body Mass Index) to enquire the level of obesity. We will tell the user his/her health status by comparing the values entered by the user with our data set. The aim of this study is to predict accurate health status using BMI. The data set consists of adults less than or equal to seventy years and will give about 98% accurate results. Our model uses BMI to predict the health status i.e., Weak, Normal, Overweight and etc. The BMI is calculated using the height, and weight of the user. The proposed study uses a machine learning approach (Random Forest and Linear Regression). We used Linear Regression and Random Forest and achieved accuracy of 84% by Linear Regression and 91% by Random Forest.
引用
收藏
页码:464 / 469
页数:6
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