AUTHOR=Blockeel Hendrik , Devos Laurens , Frénay Benoît , Nanfack Géraldin , Nijssen Siegfried TITLE=Decision trees: from efficient prediction to responsible AI JOURNAL=Frontiers in Artificial Intelligence VOLUME=6 YEAR=2023 URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2023.1124553 DOI=10.3389/frai.2023.1124553 ISSN=2624-8212 ABSTRACT=

This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, describes the broader context in which the research is situated, and summarizes strengths and weaknesses of decision trees in this context. The main goal of the article is to clarify the broad relevance to machine learning and artificial intelligence, both practical and theoretical, that decision trees still have today.