预测土耳其房地产销售价格的机器学习方法

IF 1.4 4区 工程技术
C. Çilgin, Hadi Gökçen
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引用次数: 1

摘要

买房是中低收入人群一生中最重要的决定之一。房地产市场是国民经济的一个重要因素,对个人来说也很重要。因此,预测房地产价值或房地产估值不仅对购房者有利,而且对房地产经纪人、经济学家和政策制定者都是必要的。这个问题代表了一个活跃的研究领域,因为个人、公司和政府都持有相当多的房地产资产。在这种情况下,该研究的目的是使用机器学习方法预测房地产价格,使用2021年6月和7月属于安卡拉省的房地产销售数据集。特别地,它是对机器学习回归类型方法进行全面的比较,这些方法在各种但相似的任务中给出了成功的预测结果,这些方法没有包括在房地产文献中。首先将互联网上获取的房地产数据纳入详细的数据预处理过程,然后对该数据集使用线性、Lasso和Ridge回归、XGBoost和人工神经网络(ANN)方法。根据实证研究结果,XGBoost和人工神经网络在预测房地产销售价格方面显得非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning methods for prediction real estate sales prices in Turkey
Owning 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 successful 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.
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来源期刊
Revista de la Construccion
Revista de la Construccion 工程技术-工程:土木
CiteScore
2.30
自引率
21.40%
发文量
0
期刊介绍: The Journal of Construction is aimed at professionals, constructors, academics, researchers, companies, architects, engineers, and anyone who wishes to expand and update their knowledge about construction. We therefore invite all researchers, academics, and professionals to send their contributions for assessment and possible publication in this journal. The publications are free of publication charges. OBJECTIVES The objectives of the Journal of Construction are: 1. To disseminate new knowledge in all areas related to construction (Building, Civil Works, Materials, Business, Education, etc.). 2. To provide professionals in the area with material for discussion to refresh and update their knowledge. 3. To disseminate new applied technologies in construction nationally and internationally. 4. To provide national and foreign academics with an internationally endorsed medium in which to share their knowledge and debate the topics raised.
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