Journal of computer sciences | |
Analyze and Predict the 2022 World Happiness Report Based on the Past Year's Dataset | |
article | |
Yifei Zhang1  | |
[1] School of Physical Science, University of Liverpool | |
关键词: World Happiness Report; Linear Regression; Data Analysis; Machine Learning; | |
DOI : 10.3844/jcssp.2023.483.492 | |
学科分类:计算机科学(综合) | |
来源: Science Publications | |
【 摘 要 】
Through the impact of the COVID-19, people around the world have been affected to various degrees. Thus, it is more interesting to compare the happiness reported between 2022/2021 and before 2019. This article concludes 5 years of happiness scores data including family, Gross Domestic Product (GDP), health, freedom, generosity trust, and dystopia residual. Happiness scores are considered appropriate indicators to measure the progress of social development. This study presents two linear regression models to predict happiness scores across countries in 2022. Data is sourced from the world happiness report dataset from 2015-2021, available in open source. Preliminary exploratory data analysis was carried out to select the most appropriate variables to include in the models. The models’ accuracy was tested by comparing the output values to the true 2022 world happiness report data. The experiment results show that the linear regression achieved a Root Mean Square Error (RMSE) = 0.236 and Mean Squared Error (MSE) = 0.056 for 2022.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO202307060002249ZK.pdf | 1443KB | download |