Enhancing the intelligibility of decision trees with concise and reliable probabilistic explanations

Authors

Institutions

Publication Details

Journal
Data & Knowledge Engineering
Published
2024-12-21
DOI
https://doi.org/10.1016/j.datak.2024.102394
Citations
3
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
1.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing the intelligibility of decision trees with concise and reliable probabilistic explanations

Louenas Bounia, Insaf Setitra
3 citations
Data & Knowledge Engineering
Explainable Artificial Intelligence (XAI)
1.04
article

Enhancing the intelligibility of decision trees with concise and reliable probabilistic explanations

Louenas Bounia, Insaf Setitra
article en
3 citations

Abstract

No abstract available for this paper.
Data & Knowledge EngineeringVol. 156
Université de Technologie de Compiègne (FR), Heuristics and Diagnostics for Complex Systems (FR), Université Sorbonne Paris Nord (FR), Laboratoire d'Informatique de Paris-Nord (FR)
Peace, Justice and strong institutions
Openalex Percentile: Top 18%
Explainable Artificial Intelligence (XAI)
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.