Spatial Prediction of Housing Prices in Beijing Using Machine Learning Algorithms

Ziyue Yan, Lu Zong

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

11 Citations (Scopus)

Abstract

The real estate industry places key influence on almost every aspect of social economy given its great financing capacity and prolonged upstream and downstream industry chain. Therefore, predicting housing prices is regarded as an emerging topic in the recent decades. Hedonic Regression and Machine Learning Algorithms are two main methods in this field. This study aims to explore the important explanatory features and determine an accurate mechanism to implement spatial prediction of housing prices in Beijing by incorporating a list of machine learning techniques, including XGBoost, linear regression, Random Forest Regression, Ridge and Lasso Model, bagging and boosting, based on the housing price and features data in Beijing, China. Our result shows that compared to traditional hedonic method, machine learning methods demonstrate significant improvements on the accuracy of estimation despite that they are more time-costly. Moreover, it is found that XGBoost is the most accurate model in explaining and prediciting the spatial dynamics of housing prices in Beijing.

Original languageEnglish
Title of host publicationProceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference, HPCCT 2020 and 3rd International Conference on Big Data and Artificial Intelligence, BDAI 2020
PublisherAssociation for Computing Machinery
Pages64-71
Number of pages8
ISBN (Electronic)9781450375603
DOIs
Publication statusPublished - 3 Jul 2020
Event4th High Performance Computing and Cluster Technologies Conference, HPCCT 2020 and the 3rd International Conference on Big Data and Artificial Intelligence, BDAI 2020 - Qingdao, Online, China
Duration: 3 Jul 20206 Jul 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th High Performance Computing and Cluster Technologies Conference, HPCCT 2020 and the 3rd International Conference on Big Data and Artificial Intelligence, BDAI 2020
Country/TerritoryChina
CityQingdao, Online
Period3/07/206/07/20

Keywords

  • Housing Price
  • Machine Learning Algorithms
  • Prediction
  • Spatial Modeling

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