Decision trees: from efficient prediction to responsible AI

Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack, Siegfried Nijssen

Research output: Contribution to journalReview articlepeer-review

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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.

Original languageEnglish
Article number1124553
JournalFrontiers in Artificial Intelligence
Volume6
DOIs
Publication statusPublished - 2023

Keywords

  • combinatorial optimization
  • decision trees
  • ensembles
  • explainable AI
  • learning under constraints
  • machine learning
  • responsible AI

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