Abstract
The real estate market is one of the most productive businesses in the world. In recent years, many companies are considering switching to a data-driven approach due to many technological advances. In this regard, the field of artificial intelligence stands out the most from other computer science fields. It has the potential to significantly improve buying and selling strategies, as well as to increase investment opportunities in large commercial projects. In this paper, we investigate the possibility of using two machine learning algorithms to predict real estate prices using a real-world dataset of estate listing data. We show how to prepare and analyze this dataset, and then use machine learning algorithms to accurately predict real estate sales prices. Experimental results show very promising results, thus indicating the potential of using machine learning in real-life scenarios.
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Lemeš, L., Akagic, A. (2023). Prediction of Real Estate Market Prices with Regression Algorithms. In: Ademović, N., Mujčić, E., Mulić, M., Kevrić, J., Akšamija, Z. (eds) Advanced Technologies, Systems, and Applications VII. IAT 2022. Lecture Notes in Networks and Systems, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-031-17697-5_32
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DOI: https://doi.org/10.1007/978-3-031-17697-5_32
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