Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Research on Sleep Health Prediction and Algorithms Based on Big Data

Authors
Li Mo1, *
1High School Affiliated to Shanghai Jiao Tong University, Shanghai, 200439, China
*Corresponding author. Email: mo.li.22@jdfzib.org
Corresponding Author
Li Mo
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_7How to use a DOI?
Keywords
Sleep Health Prediction; Logistic Regression; Random Forest
Abstract

Sleep helps our body recover and wake up full of power. It is also the time when we are growing, both physical and mental. Unfortunately, sleep disorders can prevent individuals from getting adequate rest. 27% of the population in the world have sleep disorders. This can affect their daytime activities. This study aims to predict sleep health using data on daily habits and body conditions and evaluate two algorithms’ performance. This study uses Logistic Regression and Random Forest. These two algorithms both perform quite excellent in prediction, so this study tries to determine which one is better and more precise. The results show that Random Forest is more suitable. Not only does Random Forest obtain a higher accuracy score, but it also attains a higher precision score. The Random Forest algorithm achieved a 93% accuracy score in predicting sleep health, with blood pressure being identified as the most important feature in prediction.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_7
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_7How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Li Mo
PY  - 2024
DA  - 2024/02/14
TI  - Research on Sleep Health Prediction and Algorithms Based on Big Data
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 55
EP  - 66
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_7
DO  - 10.2991/978-94-6463-370-2_7
ID  - Mo2024
ER  -