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Decision Rule Extraction from Binary Data Using Winning Combinations

This paper presents a new approach for making inferences about binary data. The objective is to determine rules that lead to a certain result. The method consists of four phases: in the first phase, the data is processed into a binary format of a Truth Table; in the second phase, rules are defined by utilizing an algorithm that minimizes Boolean functions (by Quine and McCluskey); in the third phase, the rules are checked and filtered; and in the fourth phase, simple rules that involve one to two features are presented.