Investigation of bagging ensembles of genetic neural networks and fuzzy systems for real estate appraisal

Authors:
Olgierd Kempa;Tadeusz Lasota;Zbigniew Telec;Bogdan Trawiński
Affiliations:
Wrocław University of Environmental and Life Sciences, Wrocław, Poland;Wrocław University of Environmental and Life Sciences, Wrocław, Poland;Wrocław University of Technology, Institute of Informatics, Wrocław, Poland;Wrocław University of Technology, Institute of Informatics, Wrocław, Poland
Venue:
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Year:
2011

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Abstract

Artificial neural networks are often used to generate real appraisal models utilized in automated valuation systems. Neural networks are widely recognized as weak learners therefore are often used to create ensemble models which provide better prediction accuracy. In the paper the investigation of bagging ensembles combining genetic neural networks as well as genetic fuzzy systems is presented. The study was conducted with a newly developed system in Matlab to generate and test hybrid and multiple models of computational intelligence using different resampling methods. The results of experiments showed that genetic neural network and fuzzy systems ensembles outperformed a pairwise comparison method used by the experts to estimate the values of residential premises over majority of datasets.