Data-Driven Real Estate Pricing: Leveraging Extra Trees Regressor for  Improved Market Predictability

Bathula Revathi, CH. Pavani, U. Chandana, K. Harish, B. Srikanth

Data-Driven Real Estate Pricing: Leveraging Extra Trees Regressor for Improved Market Predictability

Authors

Bathula Revathi, CH. Pavani, U. Chandana, K. Harish, B. Srikanth

Keywords:

Real Estate Price Prediction, Zestimate Analysis, Machine Learning, Extra Trees Regressor, Exploratory Data Analysis, Property Valuation, Housing Market Analytics

Abstract

Zestimate plays a significant role in shaping real estate market decisions, with Zillow estimatingproperty values for more than 104 million homes in the United States and influencing nearly 60% ofbuyers and sellers. Despite its widespread adoption, Zestimate has faced criticism due to valuation inaccuracies, reporting median errors

References

Agarwal, S., He, J., Sing, T. F., & Song, C. (2019b). Do real estate agents have information advantages in housing markets? Journal of Financial Economics, 134(3), 715735. https://doi.org/10.1016/j.jfineco.2019.05.008

Downloads

Published

2025-05-25

How to Cite

Bathula Revathi, CH. Pavani, U. Chandana, K. Harish, B. Srikanth. (2025). Data-Driven Real Estate Pricing: Leveraging Extra Trees Regressor for Improved Market Predictability . Journal of Computational Analysis and Applications (JoCAAA), 34(5), 406–415. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4620