Algorithms for finding logical regularities in pattern recognition

Three algorithms for finding logical regularities of classes in the precedent-based recognition problem are proposed. Logical regularities of classes are defined as conjunctions of special oneplace predicates that determine the membership of a value of a feature in a certain interval of the real axis. The conjunctions are true on as large subsets of reference objects of a certain class as possible. The problem of finding logical regularities is formulated as a special integer programming problem. Relaxation, genetic, and combinatorial algorithms are proposed for solving this problem. Comparison results for these algorithms using model and real-time problems are presented. Comparison results for various estimate evaluation recognition algorithms that use logical regularities of classes in voting procedures are also presented.