README
explainerdashboard
by: Oege Dijk
This package makes it convenient to quickly deploy a dashboard web app that explains the workings of a (scikit-learn compatible) machine learning model. The dashboard provides interactive plots on model performance, feature importances, feature contributions to individual predictions, "what if" analysis, partial dependence plots, SHAP (interaction) values, visualization of individual decision trees, etc.
You can also interactively explore components of the dashboard in a notebook/colab environment (or just launch a dashboard straight from there). Or design a dashboard with your own custom layout and explanations (thanks to the modular design of the library). And you can combine multiple dashboards into a single ExplainerHub.
Dashboards can be exported to static html directly from a running dashboard, or programmatically as an artifact as part of an automated CI/CD deployment process.
Examples deployed at: Fly.io, Hugging Face Space, detailed documentation at explainerdashboard.readthedocs.io, example notebook on how to launch dashboard for different models here, and an example notebook on how to interact with the explainer object here.