Data Mining: An Empirical Application in Real Estate Valuation

Ruben D. Jaen

This paper presents the insights gained from applying data mining techniques, in particular neural networks for the purposes of developing an intelligent model used to predict real estate property values based on variety of factors. A dataset of over one thousand transactions in real estate properties was used. The dataset included 15 variables obtained from the multiple listing system (MLS) database and captured information on transactions taking place during a period of three years. The results from applying data mining techniques to predict real estate values are promising. Future plans and recommendations for further expanding the study are given.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.