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...

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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 54; číslo 2; s. 2248 - 2260
Hlavní autori:	Lazebnik, Teddy, Bunimovich-Mendrazitsky, Svetlana, Rosenfeld, Avi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.01.2024 Springer Nature B.V
Predmet:	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
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