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International Conference on Computational Collective Intelligence

ICCCI 2013: Computational Collective Intelligence. Technologies and Applications pp 377–387Cite as

Comparison of Evolving Fuzzy Systems with an Ensemble Approach to Predict from a Data Stream

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8083))

Abstract

An approach to apply ensembles of regression models, built over the chunks of a data stream, to aid in residential premises valuation was proposed. The approach consists in incremental expanding an ensemble by systematically generated models in the course of time. The output of aged component models produced for current data is updated according to a trend function reflecting the changes of premises prices since the moment of individual model generation. The method employing general linear model, multiple layer perceptron, and radial basis function networks was empirically compared with evolving fuzzy systems designed for incremental learning from data streams.The results showed thatevolving fuzzy systems and general linear models outperformed the ensembles built using artificial neural networks.

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Author information

Authors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wybrze.eWyspia.skiego 27, 50-370, Wrocław, Poland

    Zbigniew Telec & Bogdan Trawiński

  2. Dept. of Spatial Management, Wrocław University of Environmental and Life Sciences, ul. Norwida 25/27, 50-375, Wrocław, Poland

    Tadeusz Lasota

  3. European Centre for Soft Computing, Edificio Cientifico-Tecnologico, 3a Planta, C. Gonzalo Gutierrez Quiros S/N, 33600, Mieres, Asturias, Spain

    Krzysztof Trawiński

Authors
  1. Zbigniew Telec
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  2. Bogdan Trawiński
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  3. Tadeusz Lasota
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  4. Krzysztof Trawiński
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Editor information

Editors and Affiliations

  1. Computer and Information Technology Department, University of Craiova, Bvd. Decebal 107, 200440, Craiova, Romania

    Costin Bǎdicǎ

  2. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen

  3. Computer and Information Technology Department, University of Craiova, Bvd. Decebal 107, 200440, Craiova, Romania

    Marius Brezovan

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Telec, Z., Trawiński, B., Lasota, T., Trawiński, K. (2013). Comparison of Evolving Fuzzy Systems with an Ensemble Approach to Predict from a Data Stream. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_38

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  • DOI: https://doi.org/10.1007/978-3-642-40495-5_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40494-8

  • Online ISBN: 978-3-642-40495-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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