Explainability and interpretability aren't used interchangeably.Review LaterTrueFalse
Question
Explainability and interpretability aren't used interchangeably.Review LaterTrueFalse
Solution
True. Explainability and interpretability are two different concepts in the field of machine learning and are not used interchangeably. Explainability refers to the degree to which a human can understand the decision-making process of a model, while interpretability is the degree to which a human can consistently predict a model's result. The two terms, while related, have distinct meanings.
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