Research Article Open Access

House Price Prediction: Hedonic Price Model vs. Artificial Neural Network

Visit Limsombunchai, Christopher Gan and Minsoo Lee

Abstract

The objective of this study is to empirically compare the predictive power of the hedonic model with an artificial neural network model for house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities around the house and geographical location are considered. Empirical results support the potential of artificial neural network on house price prediction, although previous studies have commented on its black box nature and achieved different conclusions.

American Journal of Applied Sciences
Volume 1 No. 3, 2004, 193-201

DOI: https://doi.org/10.3844/ajassp.2004.193.201

Submitted On: 26 April 2005 Published On: 30 September 2004

How to Cite: Limsombunchai, V., Gan, C. & Lee, M. (2004). House Price Prediction: Hedonic Price Model vs. Artificial Neural Network . American Journal of Applied Sciences, 1(3), 193-201. https://doi.org/10.3844/ajassp.2004.193.201

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Keywords

  • Hedonic Model
  • Artificial Neural Network
  • House Price