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Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics

Author

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  • Antipov, Evgeny
  • Pokryshevskaya, Elena

Abstract

To the best knowledge of authors, the use of Random forest as a potential technique for residential estate mass appraisal has been attempted for the first time. In the empirical study using data on residential apartments the method performed better than such techniques as CHAID, CART, KNN, multiple regression analysis, Artificial Neural Networks (MLP and RBF) and Boosted Trees. An approach for automatic detection of segments where a model significantly underperforms and for detecting segments with systematically under- or overestimated prediction is introduced. This segmentational approach is applicable to various expert systems including, but not limited to, those used for the mass appraisal.

Suggested Citation

  • Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:27645
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    References listed on IDEAS

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    1. Nghiep Nguyen & Al Cripps, 2001. "Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks," Journal of Real Estate Research, American Real Estate Society, vol. 22(3), pages 313-336.
    2. Carlos Martins-Filho & Okmyung Bin, 2005. "Estimation of hedonic price functions via additive nonparametric regression," Empirical Economics, Springer, vol. 30(1), pages 93-114, January.
    3. Han‐Bin Kang & Alan K. Reichert, 1991. "An Empirical Analysis of Hedonic Regression and Grid‐Adjustment Techniques in Real Estate Appraisal," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(1), pages 70-91, March.
    4. A. Prinzie & D. Van Den Poel, 2007. "Random Forrests for Multiclass classification: Random Multinomial Logit," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/435, Ghent University, Faculty of Economics and Business Administration.
    5. Gang-Zhi Fan & Seow Eng Ong & Hian Chye Koh, 2006. "Determinants of House Price: A Decision Tree Approach," Urban Studies, Urban Studies Journal Limited, vol. 43(12), pages 2301-2315, November.
    6. Carlo Bagnoli & Halbert C. Smith, 1998. "The Theory of Fuzzy Logic and its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 16(2), pages 169-200.
    7. Young-Lung Lee & Chang Jung & Yih Yeh Kuang, 2003. "Fair Evaluation of real Estate Value in Urban Area via Fuzzy Theory," ERES eres2003_198, European Real Estate Society (ERES).
    8. George H. Lentz & Ko Wang, 1998. "Residential Appraisal and the Lending Process: A Survey of Issues," Journal of Real Estate Research, American Real Estate Society, vol. 15(1), pages 11-40.
    9. Laakso, Seppo, . "Urban Housing Prices and the Demand for Housing Characteristics. A Study on Housing Prices and the Willingness to pay for Housing Characteristics and Local Public Goods in the Helsinki Metropolitan Ar," ETLA A, The Research Institute of the Finnish Economy, number 27, June.
    10. Elaine M. Worzala & Margarita Lenk & Ana Silva, 1995. "An Exploration of Neural Networks and Its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 10(2), pages 185-202.
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    Cited by:

    1. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
    2. Sebastian Gnat & Mariusz Doszyn, 2020. "Parametric and Non-parametric Methods in Mass Appraisal on Poorly Developed Real Estate Markets," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1230-1245.
    3. Jannet C. Bencure & Nitin K. Tripathi & Hiroyuki Miyazaki & Sarawut Ninsawat & Sohee Minsun Kim, 2019. "Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
    4. Mahdieh Yazdani, 2021. "Machine Learning, Deep Learning, and Hedonic Methods for Real Estate Price Prediction," Papers 2110.07151, arXiv.org.
    5. Mohammad Mirbagherijam, 2021. "Housing Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran Housing Market," Papers 2112.06192, arXiv.org.
    6. Kokot Sebastian & Gnat Sebastian, 2019. "Simulative Verification of the Possibility of using Multiple Regression Models for Real Estate Appraisal," Real Estate Management and Valuation, Sciendo, vol. 27(3), pages 109-123, September.
    7. Jungsun Kim & Jaewoong Won & Hyeongsoon Kim & Joonghyeok Heo, 2021. "Machine-Learning-Based Prediction of Land Prices in Seoul, South Korea," Sustainability, MDPI, vol. 13(23), pages 1-14, November.
    8. Kristoffer B. Birkeland & Allan D. D'Silva & Roland Füss & Are Oust, 2021. "The Predictability of House Prices: "Human Against Machine"," International Real Estate Review, Global Social Science Institute, vol. 24(2), pages 139-183.
    9. Susanna Levantesi & Gabriella Piscopo, 2020. "The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach," Risks, MDPI, vol. 8(4), pages 1-17, October.
    10. GLUMAC Brano & DES ROSIERS François, 2018. "Real estate and land property automated valuation systems: A taxonomy and conceptual model," LISER Working Paper Series 2018-09, Luxembourg Institute of Socio-Economic Research (LISER).
    11. Michalis Doumpos & Dimitrios Papastamos & Dimitrios Andritsos & Constantin Zopounidis, 2021. "Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches," Annals of Operations Research, Springer, vol. 306(1), pages 415-433, November.
    12. Mehrbakhsh Nilashi & Shahla Asadi & Rabab Ali Abumalloh & Sarminah Samad & Fahad Ghabban & Eko Supriyanto & Reem Osman, 2021. "Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    13. Marco Locurcio & Pierluigi Morano & Francesco Tajani & Felicia Di Liddo, 2020. "An Innovative GIS-Based Territorial Information Tool for the Evaluation of Corporate Properties: An Application to the Italian Context," Sustainability, MDPI, vol. 12(14), pages 1-29, July.
    14. Vladimir Vargas-Calder'on & Jorge E. Camargo, 2020. "Towards robust and speculation-reduction real estate pricing models based on a data-driven strategy," Papers 2012.09115, arXiv.org.
    15. Daikun Wang & Victor Jing Li, 2019. "Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    16. Sebastian Gnat, 2021. "Property Mass Valuation on Small Markets," Land, MDPI, vol. 10(4), pages 1-14, April.

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    More about this item

    Keywords

    Random forest; mass appraisal; CART; model diagnostics; real estate; automatic valuation model;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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