On the Coordination of Nonstrict Preferences in Machine Learning

The problem of coordination of individual preferences represented by strict and nonstrict rankings based on the Kemeny median is considered. It is shown that in order to calculate the distances between nonstrict rankings and build a loss matrix in the Kemeny algorithm, two relationship matrices are used for each ranking. As a result, the classic and new types of the Kemeny median are used to develop coordinated individual preferences.