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Weighting Component Models by Predicting from Data Streams Using Ensembles of Genetic Fuzzy Systems

  • Bogdan Trawiński
  • Tadeusz Lasota
  • Magdalena Smętek
  • Grzegorz Trawiński
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8132)

Abstract

Our recently proposed method to predict from a data stream of real estate sales transactions based on ensembles of genetic fuzzy systems was extended to include weighting component models. The method 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 techniques of weighting component models on the accuracy of an ensemble was compared in the paper. Three techniques of weighting component models were proposed: proportional to their estimated accuracy, time of ageing, and dependent on property market fluctuations.

Keywords

genetic fuzzy systems data stream sliding windows ensembles weighting component models trend functions property valuation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Bogdan Trawiński
    • 1
  • Tadeusz Lasota
    • 2
  • Magdalena Smętek
    • 1
  • Grzegorz Trawiński
    • 3
  1. 1.Institute of InformaticsWrocław University of TechnologyWrocławPoland
  2. 2.Dept. of Spatial ManagementWrocław University of Environmental and Life SciencesWrocławPoland
  3. 3.Faculty of ElectronicsWrocław University of TechnologyWrocławPoland

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