Machine learning for real estate valuation: Astana, Kazakhstan case

Barlybayev A. Sankibayev A. Niyazova R. Akimbekova G.
August 2024 Institute of Advanced Engineering and Science

Indonesian Journal of Electrical Engineering and Computer Science
2024 #35 Issue 2 1110 - 1121 pp.

Purpose of this research is to investigate the accuracy of machine learning models in forecasting and evaluating house prices, and to understand the key factors that impact pricing. The study involved analyzing data scraped from real estate ads in the “sale of secondary housing” category on the website krisha.kz. The paper emphasizes the importance of understanding the factors that affect house prices, such as quality, location, size, and building materials. It was concluded that these factors have a strong correlation with house price prediction. The information available on krisha.kz was found to be a useful resource for finding good apartments. The data collected by the scraper was analyzed by models: Linear regression (LR), interactions linear regression (ILR), robust linear regression (RLR), fine tree regression (FTR), medium tree regression (MTR), coarse tree regression (CTR), linear support vector machine (LSVM), quadratic SVM (QSVM), medium gaussian SVM (MGSVM), rational quadratic gaussian process regression (RQGPR), boosted trees (BoosT), bagged trees (BagT), neural network based on the bayesian regularization algorithm (BR-BPNN). BR-BPNN showed better results than other models, with an MSE of 32.14 and R of 0.9899.

Machine learning , Neural network , Real estate valuation criteria , Real estate value forecasting , Regression learner

Text of the article Перейти на текст статьи

Department of Artificial Intelligence Technologies, Faculty of information technologies, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
Higher School of Information Technology and Engineering, Astana International University, Astana, Kazakhstan
Department of Microbiology and Virology named after. Sh.I. Sarbasova, Faculty of dentistry, Astana Medical University, Astana, Kazakhstan

Department of Artificial Intelligence Technologies
Higher School of Information Technology and Engineering
Department of Microbiology and Virology named after. Sh.I. Sarbasova

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026