arrow
Return

Decision trees: from efficient prediction to responsible AI

delete2023-07-26
delete36
delete
OA
AI
H
Hendrik Blockeel *
L
Laurens Devos
B
Benoît Frénay‬
G
Géraldin Nanfack
S
Siegfried Nijssen
DOI:10.3389/frai.2023.1124553delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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.
Keywords:
decision trees
ensembles
responsible AI
machine learning
learning under constraints
explainable AI
combinatorial optimization
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

F
Frontiers in Artificial Intelligence
IF:
4.7
Papers:
2.3K
Citations:
4.4K

Organization

K
KU Leuven
Scholars:
5.7W
Papers: 5.2W
Citations: 8.1W
U
University of Namur
Scholars:
2.5K
Papers: 2.3K
Citations: 3.3K