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Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland

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  • Gnat Sebastian

    (Department Econometrics and Statistics, University of Szczecin, ul. Mickiewicza 64, 71-101 Szczecin, Poland)

Abstract

The study explores the application of Partial Dependence Plots (PDP) in the analysis of real estate features. The study centers on a selected real estate market in Szczecin, Poland, aiming to highlight the efficacy of PDP in understanding and interpreting the complex relationships between various features and property prices. The primary objective is to showcase the potential of PDP in capturing the nuanced interactions between real estate attributes and their impact on market prices. The CatBoost model, known for its robust handling of categorical features and strong predictive capabilities, is employed as the machine learning algorithm for this analysis. The performance of this model will be compared against a traditional multiple linear regression model, providing insights into the advantages of leveraging advanced machine learning techniques in real estate analysis. Results obtained from the analysis will be presented and discussed, shedding light on the interpretability and accuracy of the CatBoost model compared to the traditional linear regression approach. The presentation will conclude with implications for real estate practitioners and researchers, emphasizing the potential for PDP to enhance the transparency and understanding of complex models in the real estate domain. This research contributes to the growing body of knowledge on the application of advanced machine learning techniques in real estate analysis.

Suggested Citation

  • Gnat Sebastian, 2024. "Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland," Real Estate Management and Valuation, Sciendo, vol. 32(4), pages 105-116.
    • Handle: RePEc:vrs:remava:v:32:y:2024:i:4:p:105-116:n:1009
    DOI: 10.2478/remav-2024-0039
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    References listed on IDEAS

    as
    1. Raul-Tomas Mora-Garcia & Maria-Francisca Cespedes-Lopez & V. Raul Perez-Sanchez, 2022. "Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times," Land, MDPI, vol. 11(11), pages 1-32, November.
    2. Felix Lorenz & Jonas Willwersch & Marcelo Cajias & Franz Fuerst, 2023. "Interpretable machine learning for real estate market analysis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(5), pages 1178-1208, September.
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    More about this item

    Keywords

    real estate market analysis; partial dependence plots;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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