Application of Multiple Linear Regression with Regularization on Boston Housing Datasets
Authors
Yuanwei Ding1, *, Hexing Zhou2, Chak Hoi Huang3, Haoxiang Zhang4
1Qingdao No.58 High School, Qingdao, Shandong, China
2Independent Schools Foundation Academy, Hong Kong, China
3British International Shanghai School, Shanghai, China
4Eastern Christian High School, New Jersy, US
*Corresponding author.
Email: 3141205326@qq.com
Corresponding Author
Yuanwei Ding
Available Online 29 August 2024.
- DOI
- 10.2991/978-94-6463-488-4_3How to use a DOI?
- Keywords
- Linear Regression; Multiple Linear Regression; Lasso regression; Ridge regression; Machine learning
- 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.
- 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
TY - CONF AU - Yuanwei Ding AU - Hexing Zhou AU - Chak Hoi Huang AU - Haoxiang Zhang PY - 2024 DA - 2024/08/29 TI - Application of Multiple Linear Regression with Regularization on Boston Housing Datasets BT - Proceedings of the 2024 2nd International Conference on Digital Economy and Management Science (CDEMS 2024) PB - Atlantis Press SP - 14 EP - 26 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-488-4_3 DO - 10.2991/978-94-6463-488-4_3 ID - Ding2024 ER -