Chapter 1.2: Interpretation Goals

There are different reasons why machine learning models need to be interpretable. In this section we have a look at four different interpretation goals: Discover and gain global insights; understand and control individual predictions; improve, debug and audit models; justification and fairness purposes.

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• « Chapter 1.1: Introduction, Motivation, and History
• Chapter 1.3: Dimensions of Interpretability »