An algorithm to optimize explainability using feature ensembles

Feature Ensembles are a robust and effective method for finding the feature set that yields the best predictive accuracy for learning agents. However, current feature ensemble algorithms do not consider explainability as a key factor in their construction. To address this limitation, we present an a...

Full description

Bibliographic Details

Published in:	Applied intelligence (Dordrecht, Netherlands) Vol. 54; no. 2; pp. 2248 - 2260
Main Authors:	Lazebnik, Teddy, Bunimovich-Mendrazitsky, Svetlana, Rosenfeld, Avi
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.01.2024 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Computer Science Datasets Machines Manufacturing Mechanical Engineering Optimization Processes Stability Explainable AI Ensemble feature selection Optimized feature selection Machine learning
ISSN:	0924-669X, 1573-7497
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!