TY  - JOUR
AU  - Limsombunchai, Visit 
AU  - Gan, Christopher 
AU  - Lee, Minsoo 
PY  - 2004
TI  - House Price Prediction: Hedonic Price Model vs. Artificial Neural Network 
JF  - American Journal of Applied Sciences
VL  - 1
IS  - 3
DO  - 10.3844/ajassp.2004.193.201
UR  - https://thescipub.com/abstract/ajassp.2004.193.201
AB  - 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.