# FPDE

## Docs

- [API reference](https://fpde-80-mintlify-8d7c1d86.mintlify.app/api-reference.md): Reference for FPDE public classes, engine methods, prototype helpers, perturbation curves, result objects, and common error messages.
- [Examples](https://fpde-80-mintlify-8d7c1d86.mintlify.app/examples.md): FPDE usage examples for single-sample explanations, batch explanations, lambda selection, Bayesian-FPDE posteriors, and grid search.
- [Introduction](https://fpde-80-mintlify-8d7c1d86.mintlify.app/index.md): FPDE is a Python package that explains classifier predictions with prototype-contrast feature attribution for tabular feature vectors.
- [Method overview](https://fpde-80-mintlify-8d7c1d86.mintlify.app/method-overview.md): Learn how FPDE builds class prototypes, picks target and rival contrasts, and decomposes them with Diff-FPDE, Cos-FPDE, and Hyb-FPDE.
- [Quickstart](https://fpde-80-mintlify-8d7c1d86.mintlify.app/quickstart.md): Install FPDE and explain one scikit-learn classification result
- [Reproducibility checklist](https://fpde-80-mintlify-8d7c1d86.mintlify.app/reproducibility.md): Record the environment, data, model, and FPDE settings behind an experiment
- [Validation and selection](https://fpde-80-mintlify-8d7c1d86.mintlify.app/validation.md): Select Hyb-FPDE settings with grid search and perturbation curves

## Optional

- [GitHub](https://github.com/fpde-xai/fpde)
- [PyPI](https://pypi.org/project/fpde/)