Machine Learning Interpretability

This area focuses on making machine learning systems interpretable to enhance decision-making processes. It emphasizes theoretical frameworks and practical methodologies for explaining model behaviors and outcomes.

Interpretability
Machine Learning
Decision Making
Model Explanation
Causality

2,758 papers

Parent topic: Intelligent Systems and Learning

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Papers Over Time

192019401960198020002020

Top Papers

Conjunction Search Revisited.

1990 · 553 citations

Connectionist Expert Systems

1988 · 483 citations

Abductive Inference

1994 · 269 citations