Decision trees: from efficient prediction to responsible AI
Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack, Siegfried Nijssen
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.
Topics & Concepts
Decision treeSituatedStrengths and weaknessesRelevance (law)Computer scienceContext (archaeology)Artificial intelligenceMachine learningAlternating decision treeData scienceDecision tree learningManagement scienceIncremental decision treePsychologyGeographyEngineeringPolitical scienceLawSocial psychologyArchaeologyAnomaly Detection Techniques and ApplicationsImbalanced Data Classification TechniquesMachine Learning and Data Classification