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

Abstract

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.

Identifiers

DOI

10.1201/9781032684994-110

Citations and references