Development of algorithms for predictive evaluation of investment projects based on machine learning

Currently, many organizations are widely using intellectual analysis methods to effectively use large-scale data for their economic activities. Predictive analytics models help identify problems and opportunities for each customer, organization employee, or manager. In this paper, we present a model for supporting decision-making processes using predictive analytics. The concept is illustrated with an illustration of a construction company's portfolio of investment projects. The main problem is to develop a model that calculates the average price of houses in different regions of the country when building the next houses of the company. The efficiency of the regression models was analyzed.

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