Analysis and Forecast of Housing Demand Impact in China's Underdeveloped Areas Based on XGBOOST Algorithm
DOI:
https://doi.org/10.54691/bcpbm.v25i.1853Keywords:
XGBOOST, Predict, Housing demand, Influencing factorsAbstract
This paper takes China's underdeveloped areas as the research object, and takes Liangshan City, Sichuan as an example, to construct an index system of housing demand and influencing factors. On this basis, the XGBOOST algorithm and test indicators are established. By adjusting the parameters and taking the XGBOOST operation results as an example, combined with the test indicators, the results with the highest accuracy are screened out, and the independent variable importance analysis and housing demand forecast are respectively carried out to provide some inspiration and inspiration for the government. The results show that: (1) The factors affecting housing demand in underdeveloped areas mainly include real estate sales area; population growth and so on. (2) The XGBOOST algorithm constructed in this paper has good robustness and prosperous performance. The R2 is as high as 0.96 and the MSE is only 0.02. It predicts that the future housing demand will show a slow-growth trend.
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