An analysis of change trends by predicting from a data stream using genetic fuzzy systems

Authors:
Bogdan Trawiński;Tadeusz Lasota;Magdalena Smętek;Grzegorz Trawiński
Affiliations:
Institute of Informatics, Wrocław University of Technology, Wrocław, Poland;Dept. of Spatial Management, Wrocław University of Environmental and Life Sciences, Wrocław, Poland;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland;Faculty of Electronics, Wrocław University of Technology, Wrocław, Poland
Venue:
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Year:
2012

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Abstract

A method to predict from a data stream of real estate sales transactions based on ensembles of genetic fuzzy systems was proposed. The approach consists in incremental expanding an ensemble by models built over successive chunks of a data stream. The predicted prices of residential premises computed by aged component models for current data are updated according to a trend function reflecting the changes of the market. The impact of different trend functions on the accuracy of single and ensemble fuzzy models was investigated in the paper. The results proved the usefulness of ensemble approach incorporating the correction of individual component model output.