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Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches

Author

Listed:
  • Michael Doumpos

    (Technical University of Crete [Chania])

  • Dimitrios Papastamos
  • Dimitrios Andritsos
  • Constantin Zopounidis

    (Technical University of Crete [Chania], Audencia Business School)

Abstract

No abstract is available for this item.

Suggested Citation

  • Michael Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2020. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Post-Print hal-02880099, HAL.
    • Handle: RePEc:hal:journl:hal-02880099
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    Cited by:

    1. Yalpir, Sukran & Sisman, Suleyman & Akar, Ali Utku & Unel, Fatma Bunyan, 2021. "Feature selection applications and model validation for mass real estate valuation systems," Land Use Policy, Elsevier, vol. 108(C).
    2. Wojciech Kisiała & Izabela Rącka, 2021. "Spatial and Statistical Analysis of Urban Poverty for Sustainable City Development," Sustainability, MDPI, vol. 13(2), pages 1-18, January.
    3. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).
    4. Dieudonné Tchuente & Serge Nyawa, 2022. "Real estate price estimation in French cities using geocoding and machine learning," Annals of Operations Research, Springer, vol. 308(1), pages 571-608, January.
    5. Stanislav Endel & Marek Teichmann & Dagmar Kutá, 2020. "Possibilities of House Valuation Automation in the Czech Republic," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    6. Tomić, Hrvoje & Ivić, Siniša Mastelić & Roić, Miodrag & Šiško, Josip, 2021. "Developing an efficient property valuation system using the LADM valuation information model: A Croatian case study," Land Use Policy, Elsevier, vol. 104(C).

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