ExplainReduce is a global, model-agnostic, and post-hoc explanation method that extracts a small set of 'proxies' from a large collection of local models generated by local explanation methods (e.g., LIME and SHAP). Each proxy is a representative local model that effectively captures the prediction behaviour of the black-box model within a specific neighbourhood. The set of proxies summarizes the black-box model's decision pattern across different regions of the input space, facilitating global interpretability.
To install python, follow the instructions from the official website of Python. To install the package, follow the instructions:
- Create a virtual environment (Optional)
# Create a virtual environment python -m venv venv # Activate the environment # Windows: .\venv\Scripts\activate # macOS/Linux: source venv/bin/activate
- Clone the repository
git clone $url_of_this_repository_from_github cd explainreduce
- Install dependencies
pip install -r requirements.txt
A simple example of the idea behind ExplainReduce. A black-box model (left) can have many local explanations (middle), but ExplainReduce can reduce the size of the local explanation set to get a global explanation consisting of two simple models (right).
