Decision trees: From efficient prediction to responsible AI | Geraldin Nanfack

Decision trees: From efficient prediction to responsible AI

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.

Publication
Frontiers in Artificial Intelligence, section Machine Learning and Artificial Intelligence
Geraldin Nanfack
Geraldin Nanfack
Postdoctoral Researcher

My research interests include constraints in machine learning, interpretability and trustworthiness.

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