Skip to main content

Official implementation of GNNFairViz

Project description

GNNFairViz

Build Status License

Overview

GNNFairViz is a visualization tool designed to provide insights into the fairness of Graph Neural Networks from the perspective of data.

Installation

You can install GNNFairViz using pip or from source.

Using pip

pip install GNNFairViz

From Source

git clone https://github.com/xinwuye/GNNFairViz.git
cd GNNFairViz
pip install .

Usage

Examples of how to use the package can be found in the evaluation/cases folder.

Features

  • Support customizing and inspecting fairness through various viewpoints.
  • Provide clues and interactions for node selection to analyze how they affect model bias.
  • Allow diagnosing GNN fairness issues in an interactive manner.

Contributing

We welcome contributions! Follow these steps to set up your development environment and contribute to the project.

Setting Up the Development Environment

git clone https://github.com/xinwuye/GNNFairViz.git
cd GNNFairViz
poetry install

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or support, please contact:

Credits

This project uses and adapts code from the following repositories:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gnnfairviz-0.0.0.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

gnnfairviz-0.0.0-py3-none-any.whl (34.7 kB view details)

Uploaded Python 3

File details

Details for the file gnnfairviz-0.0.0.tar.gz.

File metadata

  • Download URL: gnnfairviz-0.0.0.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.9

File hashes

Hashes for gnnfairviz-0.0.0.tar.gz
Algorithm Hash digest
SHA256 b0db01e9bc62a4e294802af2717d77f858d9d1eb8823bb54bbb7c6e12391b37e
MD5 f41b7188d9a6ed2623d0fc3b413df09d
BLAKE2b-256 114ce4c09c5b3744002cf29cddbad537130d10a5adf994d8e32a475500187d2c

See more details on using hashes here.

File details

Details for the file gnnfairviz-0.0.0-py3-none-any.whl.

File metadata

  • Download URL: gnnfairviz-0.0.0-py3-none-any.whl
  • Upload date:
  • Size: 34.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.9

File hashes

Hashes for gnnfairviz-0.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 bfc7ff79a7556fbbcd21f0cfd7d62af202150dd68fd8d2b493ae1eb3f6ab9112
MD5 dbc6bff44bbcef047916599888adc2c5
BLAKE2b-256 193c038eba03c565ee911e536b5ca2eb52b5b55fb379f24c920d6e1216a0d232

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page