XAI-Units

This is a library to help benchmark and compare explainable AI feature attribution methods. It contains a collection of datasets and models with specific units of behaviour that are known to be challenging for feature attribution methods. The library also contains an end-to-end pipeline for applying feature attribution methods across a range of datasets/models, scoring them with metrics, then summarising the results.

Contents:

• Quickstart - Library Walkthrough
  • Main Features
• Image Dataset Example
• Customization Tutorial
  • 1 Custom Datasets
  • 2 Custom Methods
• API Reference
  • model
  • methods
  • trainer
  • metrics
  • pipeline
  • fine_tune
  • common_lib
  • datagenerator

Indices and tables

• Index

• Module Index

• Search Page