Unofficial Repository for AD Fair Classification
The installation of our project is super easy.
Step 1: Clone the codebase, and compile this codebase:
# Clone the codebase
git clone https://github.com/GT-111/AD.git
Step 2: Create a python environment for the project
conda create --name AD python=3.8 -y
conda activate AD
Step 3: Install the required packages
pip install -r requirements.txt
Then you are all set.
To make it easy and clear to perform modifications on the experiment setting, most of the settings can be done by setting the YAML file in ./config directory. One sample configuration file is provided.
To make it easy for future development, we built a clear pipeline including dataset splitting, data preprocessing, modeling training and evaluation. All core functions lie in a simple jupyter notebook.