Machine learning methods for prediction real estate sales prices in Turkey

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dc.authorid0000-0002-8983-118Xen_US
dc.authorid0000-0002-5163-0008en_US
dc.contributor.authorÇılgın, Cihan
dc.contributor.authorGökçen, Hadi
dc.date.accessioned2023-09-04T06:07:06Z
dc.date.available2023-09-04T06:07:06Z
dc.date.issued2023en_US
dc.departmentBAİBÜ, Gerede Uygulamalı Bilimler Fakültesi, Yönetim Bilişim Sistemleri Bölümüen_US
dc.description.abstractOwning a house is one of the most important decisions that low and middle income people make in their lives. The real estate market is a significant factor of the national economy as much as it is important for individuals. Therefore, predicting real estate values or real estate valuation is beneficial and necessary not only for buyers, but also for real estate agents, economists and policy makers. This issue represents an active area of research, as individuals, companies and governments hold considerable assets in real estate. In this context, the aim of the study is to predict real estate prices with Machine Learning methods using the real estate sales data set in June and July 2021 belonging to the province of Ankara. In particular, it is to perform a comprehensive comparison on Machine Learning regression types methods that give suc-cessful prediction results in various but similar tasks, which are not included in the real estate literature. Real estate data obtained over the Internet was first included in a detailed data preprocessing process, and then Linear, Lasso and Ridge Regression, XGBoost and Artificial Neural Networks (ANN) methods were used on this dataset. According to empirical findings, XGBoost and ANNs appear as very important alternatives in predicting real estate sales prices.en_US
dc.identifier.citationÇılgın, C., & Gökçen, H. (2023). Machine learning methods for prediction real estate sales prices in Turkey. Revista de la construcción, 22(1), 163-177.en_US
dc.identifier.doi10.7764/RDLC.22.1.163
dc.identifier.endpage177en_US
dc.identifier.issn0718-915X
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85159117851en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage163en_US
dc.identifier.urihttp://dx.doi.org/10.7764/RDLC.22.1.163
dc.identifier.urihttps://hdl.handle.net/20.500.12491/11638
dc.identifier.volume22en_US
dc.identifier.wosWOS:001011250700011en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÇılgın, Cihan
dc.language.isoenen_US
dc.publisherPontificia Univ Catolica Chile, Escuela Construccion Civilen_US
dc.relation.ispartofRevista De La Construccionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMachine Learningen_US
dc.subjectNeural Networksen_US
dc.subjectReal Estate Priceen_US
dc.subjectPredictionen_US
dc.subjectAnkaraen_US
dc.subjectRegressionen_US
dc.titleMachine learning methods for prediction real estate sales prices in Turkeyen_US
dc.typeArticleen_US

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