Abstract
Among many factors influencing the prices of building plots in rural areas, one can distinguish location factors related to the proximity and availability of many public services and transport hubs, as well as environmental factors, which are mainly related to the proximity of forests, parks or rivers. This paper examines how strongly such attributes of a property influence its price in rural areas. The experiments were carried out using top-notch machine learning methods and real-world data derived from the real estate price register and publicly available geographical data sets. The study showed that environmental features of building plots in a rural area had rather a small impact on their prices whereas location features turned out to be more important.
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Piwowarczyk, M., Lasota, T., Telec, Z., Trawiński, B. (2019). Valuation of Building Plots in a Rural Area Using Machine Learning Approach. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11683. Springer, Cham. https://doi.org/10.1007/978-3-030-28377-3_31
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