Literature Review of Explainable Machine Learning in Real Estate

Joint Proceedings of Baltic DB&IS Conference Forum and Doctoral Consortium 2024 co-located with 16th International Baltic Conference on Digital Business and Intelligent Systems (Baltic DB&IS 2024) 2024
Arnis Staško, Jānis Grundspeņķis

A literature review is conducted on explainable machine learning methods used in real estate. It identifies 17 relevant articles that reveal various subfields of real estate and the explainable machine learning methods used. Among them, XGBoost and SHAP is the most commonly used combination for explainable machine learning in the studied area. The study also identifies research gaps that could be addressed through further studies on time factors, model explainability, training set balance, and causal dependencies.

Keywords
Explainable machine learning, Literature review, Real estate, Research methods
Hyperlink
https://ceur-ws.org/Vol-3698/paper6.pdf

Staško, A., Grundspeņķis, J. Literature Review of Explainable Machine Learning in Real Estate. In: Joint Proceedings of Baltic DB&IS Conference Forum and Doctoral Consortium 2024 co-located with 16th International Baltic Conference on Digital Business and Intelligent Systems (Baltic DB&IS 2024), Lithuania, Vilnius, 30 Jun-3 Jul., 2024. Aachen: RWTH, 2024, pp.58-72. ISSN 1613-0073.

Publication language
English (en)