# Construction of Decision Trees and Acyclic Decision Graphs from Decision Rule Systems

arXiv: https://arxiv.org/abs/2305.01721 · HTML: https://mlsanity.com/paper/2305.01721/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 47 references that are in the map.
- First posted on arXiv 2 May 2023.

## Built on by (most cited first, 1 of 1)

- [Greedy Algorithm for Inference of Decision Trees from Decision Rule Systems](https://mlsanity.com/paper/2401.06793/) (2024)

## Abstract (arXiv)

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.