Analysis of USA National Home Prices Based on Different Machine Learning Models

Yujie Li ()
Additional contact information
Yujie Li: Sun Yat-Sen University, Sun Yat-Sen University Cancer Center

A chapter in Proceedings of the 2024 9th International Conference on Social Sciences and Economic Development (ICSSED 2024), 2024, pp 100-109 from Springer

Abstract: Abstract Numerous nations rely heavily on the real estate industry, and changes in home prices have a big impact on people’s quality of life. On this basis, house price prediction plays an important role in the economic field, e.g., making economic policy. Affected by thousands of potential factors, it is complicated to estimate the house price accurately. This study uses several machine learning models to build the relationship between 5 different factors of macro perspective with house prices in the US and managed to predict the real estate price. Among these models, the Decision tree model, KNN model, and Neural network model all perform high fitting effects and stable generalization activity. The SVR model is also suitable for this case. The article also indicates that the MLR model shows the worst fitting effect because of being limited in capturing the non-linear characters in datasets. Overall, these results provide accurate house price prediction models, which may be very valuable in real property sectors.

Keywords: Economy; house price prediction; machine learning (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-459-4_13

Ordering information: This item can be ordered from
http://www.springer.com/9789464634594

DOI: 10.2991/978-94-6463-459-4_13

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().