<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Construction sector has an important place in Turkey’s economy. Real estate sales for the sector are increasing in parallel. However, the purchase cost is also important for those who are willing to buy a real estate. In the acquisition of real estate, factors such as size, location and age of the house are taken into consideration. The aim of the article is to conduct research on factors affecting real estate values by data mining. In this study, the most important variables that determine the value of the real estate have been investigated by data mining methods. The research has been carried out in Karabük and the variables determined according to the opinions of real estate experts. As classification methods, CHAID and C&amp;RT algorithms have been used. It has been evaluated that both algorithm estimation results can be used. Within the framework of the study, the variables that have the most impact on the unit price have been determined, such as the size of the real estate, the distance to the city centre, the popularity, and the age of the building. The use of advanced technologies, such as statistical modelling and machine learning in real estate valuation and automatic value estimation, is of importance in determining the real value of the real estate.</p></abstract>

Construction sector has an important place in Turkey’s economy. Real estate sales for the sector are increasing in parallel. However, the purchase cost is also important for those who are willing to buy a real estate. In the acquisition of real estate, factors such as size, location and age of the house are taken into consideration. The aim of the article is to conduct research on factors affecting real estate values by data mining. In this study, the most important variables that determine the value of the real estate have been investigated by data mining methods. The research has been carried out in Karabük and the variables determined according to the opinions of real estate experts. As classification methods, CHAID and C&RT algorithms have been used. It has been evaluated that both algorithm estimation results can be used. Within the framework of the study, the variables that have the most impact on the unit price have been determined, such as the size of the real estate, the distance to the city centre, the popularity, and the age of the building. The use of advanced technologies, such as statistical modelling and machine learning in real estate valuation and automatic value estimation, is of importance in determining the real value of the real estate.

Research on Factors Affecting Real Estate Values by Data Mining

Baltic Journal of Real Estate Economics and Construction Management

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Research on Factors Affecting Real Estate Values by Data Mining"}

Construction sector has an important place in Turkey’s economy. Real estate sales for the sector are increasing in parallel. However, the purchase cost is also...

Research on Factors Affecting Real Estate Values by Data Mining

Publié en ligne: 13 déc. 2018

Pages: 220 - 239

DOI: https://doi.org/10.2478/bjreecm-2018-0017

Mots clés
CHAID, classification, construction sector, C&RT, data mining, decision tree, real estate valuation

© 2018 Filiz Ersoz, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Research on Factors Affecting Real Estate Values by Data Mining

Publié en ligne: 13 déc. 2018

Pages: 220 - 239

DOI: https://doi.org/10.2478/bjreecm-2018-0017

Mots clésCHAID, classification, construction sector, C&RT, data mining, decision tree, real estate valuation

© 2018 Filiz Ersoz, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Mots clés
CHAID, classification, construction sector, C&RT, data mining, decision tree, real estate valuation