MODELS AND INFORMATION TECHNOLOGY FOR REAL ESTATE VALUATION USING MACHINE LEARNING ALGORITHMS

Abstract

It has been established that one of the main challenges in the field of real
estate valuation is processing large volumes of information. Traditional valuation
methods, which rely on expert experience, can be limited and prone to human error. The
application of Data Science enables the automation of data collection, analysis, and
processing, leading to more accurate and objective results. The article explores the
development of Data Science technology for real estate valuation, including data analysis,
the use of statistical methods and machine learning techniques, and the creation of a
valuation model based on the obtained results. Existing approaches to the use of
analytical methods in real estate valuation tasks are examined. A new methodology for
their application is developed, along with a justification of the feasibility and necessity
of implementing the proposed methodology. Recommendations for the practical
implementation of the methodology are provided.