> For the complete documentation index, see [llms.txt](https://subramanian-pr.gitbook.io/research-paper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://subramanian-pr.gitbook.io/research-paper/3.-interpretable-machine-learning/3.1-definition.md).

# 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)](https://2557836893-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MBG9ZgmYOMHGydWe7ko%2F-MEZgr3jmu68hyzipt-d%2F-MEZh4gTDBrrz9ul_PRh%2Fimage.png?alt=media\&token=1ee31ee4-b2a1-4e3f-8bf6-f32e4ddb05ea)