Greedy Algorithm for Inference of Decision Trees from Decision Rule Systems

Decision trees [3, 4, 8, 31, 34, 40] and systems of decision rules [6, 7, 11, 14, 33, 34, 35, 36] are widely used as classifiers, knowledge representation tools, and algorithms. They are known for their interpretability in data analysis [10, 15, 23, 41]. Investigating the relationship between these two models is an important task in computer science. Converting decision trees into decision rule systems is a well-known and simple process [37, 38, 39]. This paper focuses on the inverse transformation problem, which is not trivial. The research related to this problem encompasses several directions: Two-stage construction of decision trees. This approach involves building decision rules based on input data, followed by the construction of decision trees or decision structures (which are generalizations of decision trees) using the generated rules. The benefits of this two-stage construction method are explained in [1, 2, 17, 18, 19, 20, 21, 22, 42].