Application of Random Forest in the analysis of students' physical health test data

Authors

  • Dongxu Li School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China
  • Ping Zhang School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China
  • Yuren Zhang School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China
  • Tianlong Xiao School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China

DOI

https://doi.org/10.52810/TC.2021.100040

Keywords:

Random Forest, Bagging, Data mining, Physical health data

Abstract

The physical fitness test data of college students is an important basis to measure the physical fitness level of college students. The application of data mining techniques to the deep mining of physical fitness data plays an important role in the physical health development of college students and the design of physical education programs. Based on the Random Forest classification algorithm, this study analyzed and explored the potential factors affecting students' physical test scores by using the physical fitness test data of the 2019 grade undergraduates of Baoji College of Arts and Sciences, and scientifically predicted the physical fitness status of college students according to the analysis results, and provided scientific guidance for physical exercise according to the analysis and prediction results. The experimental results show that the Random Forest classifier selected in this experiment has high accuracy and can provide a decision basis for the guidance of scientific physical exercise for college students.

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Author Biographies

Dongxu Li, School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China

Dongxu Li Graduated with B.S at the Department of Computer of Baoji University of Arts and Sciences from 2018 to 2022. His current research interests include machine learning and computer vision.

Ping Zhang, School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China

Ping Zhang  Graduated with M.S at the Department of Computer and Information Science of Liaoning Normal University from 2008 to 2011. He is a lecturer in Baoji University of Arts and Sciences. His current research interests include bioinformatics machine learning and graph neural network.

Yuren Zhang, School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China

Yuren   Zhang  Master of social, Lecturer. Graduated from the Xi’an Technological University in 2011. Now he works in  Baoji University of Arts and Science. He research interests include Image processing and pattern recognition.

Tianlong Xiao, School of Computer, Bao Ji University of Arts and Sciences, Baoji 721016, China

Tianlong Xiao  Graduated with B.S at the Department of Computer of Baoji University of Arts and Sciences from 2018 to 2022. His current research interests include machine learning and computer vision.

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Application of Random Forest in the analysis of physical health test data of college students

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Published

2021-09-06

How to Cite

Li, D., Zhang, P., Zhang, Y., & Xiao, T. (2021). Application of Random Forest in the analysis of students’ physical health test data. ASP Transactions on Computers, 1(2), 7–11. https://doi.org/10.52810/TC.2021.100040

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Section

Regular Paper