Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)

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Happiness Index Prediction Using Hybrid Regression Model

Authors
Yuning Han1, Yichen Shao2, *, Yazhuo Zhang3, 4
1School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, 611731, China
2School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China
3School of Natural Science, University of International Business and Economics, Beijing, China
4University of Manchester, Manchester, M13 9LP, UK
*Corresponding author. Email: syc_bupt@bupt.edu.cn
Corresponding Author
Yichen Shao
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-198-2_9How to use a DOI?
Keywords
Happiness prediction; XGBoost; CatBoost; Gradient Boosting; Model fusion with weighted averaging
Abstract

In the field of social science, research on happiness combines multiple subjects like philosophy, psychology, sociology and economics, and plays an essential role in national health. In this report, with the publicly available questionnaire results, we select multiple sets of variables, including individual variables family variables, social attitudes, to predict its evaluation of happiness. During data preprocessing, imputation, and outlier processing, binning and the one-hot encoder were applied to stabilize and rationalize the data. As for the prediction algorithms, Extreme Gradient Boosting (XGBoost), CatBoost, and Gradient Boosting Regressor are put into use, and then we put forward the weighted average methods to fuse the models and reach the final results. In the final results, we discovered that all the features are significantly related to the happiness index, in which being depressed for a long time, lack of exercise, or being in a toxic social environment may all have severe unfavorable effects on the level of happiness. It is worth stressing that such research on happiness can help optimize the allocation of resources and the application of certain policies in order to raise the domestic happiness level, which is of great impact on both the economy and our whole society.

Copyright
© 2023 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 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
10 August 2023
ISBN
978-94-6463-198-2
ISSN
2589-4900
DOI
10.2991/978-94-6463-198-2_9How to use a DOI?
Copyright
© 2023 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  - Yuning Han
AU  - Yichen Shao
AU  - Yazhuo Zhang
PY  - 2023
DA  - 2023/08/10
TI  - Happiness Index Prediction Using Hybrid Regression Model
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 76
EP  - 87
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_9
DO  - 10.2991/978-94-6463-198-2_9
ID  - Han2023
ER  -