XAISuite 0.8.3.3

XAISuite: Training and Explanation Generation Utilities for Machine Learning Models

XAISuite: Training and Explaining Machine Learning Models

Table of Contents

1. Introduction
2. Installation
3. Getting Started
4. How to Contribute
5. Technical Report and Citing XAISuite

Introduction

XAISuite (Explanatory Artificial Intelligence Suite) is a library for training and explaining machine learning models for tabular datasets in Python. It provides a unified interface for training any sklearn model using just a line of code and allows users to easily compare the results of different explainers!

XAISuite accomplishes machine learning model training and explanation generation in three steps: (1) data loading, (2) model training and (3) explanation generation. Each of these steps are delved into more detail in our documentation and in the demo tutorials.

XAISuite was created as a helper library to [this paper](insert link), which studied the difference in SHAP and LIME explanations for different models on tabular datasets.

Installation

You can install the XAI Suite through PyPI:

pip install XAISuite

Getting Started

For example code and an introduction to the library, see the Demo Folder.

If you are looking for a model or dataset to use, sklearn has several cool options.

How to Contribute

We welcome the contribution from the open-source community to improve the library!

To add a new functionality into the library or point out a flaw, please create a new issue on Github. We'll try to look into your requests as soon as we can.

Technical Report and Citing XAISuite

A paper proposing and using XAISuite to compare explanatory methods is still in pre-publication. Use the following BibTex to cite XAISuite:

@article{mitra2022-xaisuite,
  author    = {Shreyan Mitra and Leilani Gilpin},
  title     = {Comparison of SHAP and LIME Explanations for Supervised
Machine Learning Models Trained on Tabular Datasets},
  year      = {2022},
  doi       = {},
  url       = {},
  archivePrefix = {},
  eprint    = {},
}

Contact Us

If you have any questions, comments or suggestions, please do not hesitate to contact us at [e-mail]

License

This work is licensed under a BSD 3-Clause License.