From: FLAIRS-02 Proceedings. Copyright © 2002, AAAI (www.aaai.org). All rights reserved.
Data Mining: An Empirical Application in Real Estate Valuation Ruben D. Jaen
Florida International University
University Park, PC236
Miami, Fl 33199
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.
Keywords: Data mining, real estate valuations, home
The factors that determine housing prices are of interest to urban planners, developers, real estate professionals, and
financial executives as well as most American
homeowners. According to a 1998 Federal Reserve survey
(Kennickell, et al., 2000), 66.2 percent of U.S. households
are homeowners and housing investment amounts to 33
percent of household net worth. The number of new
home sales as well as home resales are an important
component of the U.S. economy and data concerning these
transactions is closely tracked for the purpose of gauging
economic activity and formulating appropriate monetary
and fiscal policies. This paper examines the factors that
determine housing prices in a sample of over 1000 home
sales in Miami-Dade County during the period of 19992001.
Sales of homes take place in the marketplace dictated by
the usual rules of supply and demand. Since this is not a
perfect market, there is a great latitude for judgment in...
References: Abraham, J.M. and P.H. Hendershott. 1996. “Bubbles in
Metropolitan Housing Markets.” Journal of Housing
Bartik, T.J. 1991. Who Benefits from State and Local
Economic Development Policies? (Kalamazoo, Michigan:
Gilbertson, Barry, 2001. “Appraisal or Valuation: An Art
or a Science?” Real Estate Issues 26(3): 86-90.
Ludvigson, S. and C. Steindel. 1999. “How Important is
the Stock Market Effect on Consumption?” Federal
Malpezzi, S. 1996. “Housing Prices, Externalities, and
Regulation in U.S
Malpezzi, S., G. H. Chun, and R. K. Green. 1998. “New
Place-to-Place Housing Price Indexes for U.S.
Pindyck, R. S. and D. L. Rubinfeld. 1981. Econometric
Models and Economic Forecasts
Poterba, J.M. 1991. “House Price Dynamics: The Role of
Tax Policy and Demography.” Brookings Papers on
Poterba, J.M. 2000.
Rose, L.A. 1989. “Topographical Constraints and Urban
Land Supply Indexes.” Journal of Urban Economics.
Segal, D. and P. Srinivasan. 1985. “The Impact of
Suburban Growth Restrictions on U.S
Inflation, 1975-78.” Urban Geography 6(l): 14-26.
Starr-McCluer, M. 1998. “Stock Market Wealth and
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