3.1 Definition

An interpretable model helps you to understand and account for the factors that are (not) included in the model and account for the context of the problem when taking actions based on model predictions. Improving generalization and performance. High interpretability typically leads to a model that generalizes better.

Flow for an Interpretable Models (Ref. https://christophm.github.io/interpretable-ml-book/agnostic.html)