Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review

Explainability and interpretability have emerged as essential considerations in machine learning, particularly as models become more complex and integral to a wide range of applications. In response to increasing concerns over opaque “black-box” solutions, the literature has seen a shift toward two...

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發表在:	Algorithms
Main Authors:	Daniele Pelosi, Diletta Cacciagrano, Marco Piangerelli
格式:	Article
語言:	英语
出版:	MDPI AG 2025-07-01
主題:	explainability explainable AI interpretability interpretable AI concept drift data drift
在線閱讀:	https://www.mdpi.com/1999-4893/18/7/443