Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland
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 fe...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-12-01
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| Series: | Real Estate Management and Valuation |
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| Online Access: | https://doi.org/10.2478/remav-2024-0039 |
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| author | Gnat Sebastian |
| author_facet | Gnat Sebastian |
| author_sort | Gnat Sebastian |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e80e1ad8484443108efb227ee7fcedc8 |
| institution | DOAJ |
| issn | 2300-5289 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Real Estate Management and Valuation |
| spelling | doaj-art-e80e1ad8484443108efb227ee7fcedc82025-08-20T02:57:40ZengSciendoReal Estate Management and Valuation2300-52892024-12-0132410511610.2478/remav-2024-0039Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, PolandGnat Sebastian0Department Econometrics and Statistics, University of Szczecin, ul. Mickiewicza 64, 71-101Szczecin, PolandThe 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.https://doi.org/10.2478/remav-2024-0039real estate market analysispartial dependence plotsc10r30 |
| spellingShingle | Gnat Sebastian Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland Real Estate Management and Valuation real estate market analysis partial dependence plots c10 r30 |
| title | Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland |
| title_full | Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland |
| title_fullStr | Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland |
| title_full_unstemmed | Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland |
| title_short | Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland |
| title_sort | determining the influence of real estate features on prices with partial dependence plots a case study in szczecin poland |
| topic | real estate market analysis partial dependence plots c10 r30 |
| url | https://doi.org/10.2478/remav-2024-0039 |
| work_keys_str_mv | AT gnatsebastian determiningtheinfluenceofrealestatefeaturesonpriceswithpartialdependenceplotsacasestudyinszczecinpoland |