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Interpretable machine learning: Fundamental principles and 10 grand challenges

Cynthia D Rudin; Chaofan Chen; Zhi Chen dkk.

Statistics Surveys · 2022 · Inggris · OpenAlex Scopus

Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting. In this work, we provide fundamental principles for interpretable ML, and dispel common misunderstandings that dilute the importance of this crucial topic. We also identify 10 technical challenge…