Using multivalued logic for qualitative data analysis

The article considers a logical approach to data analysis for solving the classification problem. The studied data is a set of objects and their features. As a rule, this is disparate heterogeneous information, and it is not enough for a reasonable application of probabilistic models. Therefore, logical algorithms are considered, which, under certain conditions, may be more adequate. For an expressive formal representation of the relationship between objects and their attributes, multivalued logic is used, and the number of values depends on the particular attribute. Therefore, a system of operations on variables with different domains is proposed. As a result, a decision function is built, which is a classifier of objects present in the studied data. The properties and possibilities of this function are analyzed. It is shown that a logical function, which is a conjunction in the space of rules that connect given objects with their characteristic features, unambiguously characterizes the initial data, divides the subject area into classes, has modifiability properties, satisfies the requirements of completeness and consistency in the given area. The paper also proposes an algorithm for its implementation.