C-SHAP: A Hybrid Method for Fast and Efficient Interpretability

C-SHAP: A Hybrid Method for Fast and Efficient Interpretability

Model interpretability is essential in machine learning, particularly for applications in critical fields like healthcare, where understanding model decisions is paramount. While SHAP (SHapley Additive exPlanations) has proven to be a robust tool for explaining machine learning predictions, its high...

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Bibliographic Details
Main Authors: Golshid Ranjbaran, Diego Reforgiato Recupero, Chanchal K. Roy, Kevin A. Schneider
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
interpretability in machine learning
interpretability
SHAP
LIME
C-SHAP
computational efficiency
Online Access:https://www.mdpi.com/2076-3417/15/2/672
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