Decision trees and systems of decision rules are widely used as classifiers, as a means for knowledge representation, and as algorithms. They are among the most interpretable models for data analysis. The study of the relationships between these two models can be seen as an important task of computer science. Methods for transforming decision trees into systems of decision rules are simple and well-known. In this paper, we consider the inverse transformation problem, which is not trivial. We study the complexity of constructing decision trees and acyclic decision graphs representing decision trees from decision rule systems, and we discuss the possibility of not building the entire decision tree, but describing the computation path in this tree for the given input.

翻译：决策树和决策规则系统被广泛用作分类器、知识表示手段以及算法。它们是数据分析中最具可解释性的模型之一。研究这两种模型之间的关系可视为计算机科学的一项重要任务。将决策树转化为决策规则系统的方法简单且广为人知。本文考虑逆变换问题，该问题并非平凡。我们研究了从决策规则系统中构建决策树及表示决策树的无环决策图的复杂性，并探讨了无需构建完整决策树，而仅针对给定输入描述该树中计算路径的可能性。