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Examining the Relationship Between Foreigners in China Food Delicacies Using Multiple Linear Regression Analysis (sklean)

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

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Abstract

The availability of some specific foods and the nutrients in foods have a great impact on everyone’s life. It goes to the extent of being among the determining factors of an individual’s long-term stay in a foreign country. In this paper, we examine the relationship between the long-term stay of foreigners in China and their food delicacies. For the analysis of data (data from administered questionnaires and interviews), a model was built using python with sklearn in multiple regression, with the coefficient, the intercept, and the adjusted r-square well examined. The research shows a correlation between foreigners living in China and their food delicacies, indicating that though foreigners consider the nutritional and health benefits of cuisine, the taste of the cuisine is prioritized, making their living conditions somewhat difficult when choosing a nutritious cuisine.

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Acknowledgement

This Research work was supported in part by 2019 Anhui Provincial Natural Science Foundation Project (Grant No. 1908085MF189), in part by 2018 Cultivation Project of Top Talent in Anhui Colleges and Universities (Grant No. gxbjZD15).

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Correspondence to Shunxiang Zhang .

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Asimeng, E., Zhang, S., Esther, A., Li, M. (2021). Examining the Relationship Between Foreigners in China Food Delicacies Using Multiple Linear Regression Analysis (sklean). In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_271

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_271

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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