Hybrid Classifier of Recommender Systems Based on Quantum Methods for Decision Trees

In this paper, we discuss an purpose, construction mechanism and practical application of classical-quantum decision trees in the process of constructing hybrid classical-quantum decision forests. Traditional computational mechanisms are good at processing data about currently used data storage capacity units. Looking at the speed of growth and the amount of new data owing in, as well as the need to archive historical data, it will soon be necessary to resort to quantum representations of classical methods implemented on quantum computers. The article discusses the practical implementation of quantum recommendation circuits for profiling users of the system.