Application of Multiple Linear Regression with Regularization on Boston Housing Datasets

Yuanwei Ding (), Hexing Zhou (), Chak Hoi Huang () and Haoxiang Zhang ()
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Yuanwei Ding: Qingdao No.58 High School
Hexing Zhou: Independent Schools Foundation Academy
Chak Hoi Huang: British International Shanghai School
Haoxiang Zhang: Eastern Christian High School

A chapter in Proceedings of the 2024 2nd International Conference on Digital Economy and Management Science (CDEMS 2024), 2024, pp 14-26 from Springer

Abstract: Abstract This paper first introduces the principle of multi-objective linear regression, and studies the Boston housing price data set with regularized multiple linear regression. Then this paper combines the knowledge of machine learning to build a prediction model. In the final forecast of the Boston house price, it was about 78 percent accurate compared to the real house price.

Keywords: Linear Regression; Multiple Linear Regression; Lasso regression; Ridge regression; Machine learning (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-488-4_3

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DOI: 10.2991/978-94-6463-488-4_3

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