🔬 dnn-inf: significance tests of feature relevance for a black-box model

dnn-inf is a Python module for hypothesis testing based on black-box models, including deep neural networks.

• GitHub repo: https://github.com/statmlben/dnn-inference
• Documentation: https://dnn-inference.readthedocs.io
• PyPi: https://pypi.org/project/dnn-inference
• Open Source: MIT license
• Paper: arXiv:2103.04985

Installation

Dependencies

dnn-inference requires: Python>=3.8 + requirements.txt

pip install -r requirements.txt

User installation

Install dnn-inference using pip

pip install dnn_inference
pip install git+https://github.com/statmlben/dnn-inference.git

Reference

If you use this code please star the repository and cite the following paper:

@article{dai2022significance,
   title={Significance Tests of Feature Relevance for a Black-Box Learner},
   author={Dai, Ben and Shen, Xiaotong and Pan, Wei},
   journal={IEEE Transactions on Neural Networks and Learning Systems},
   year={2022},
   publisher={IEEE}
}

Notebook

• MNIST dataset: Notebook1
• Boston house prices dataset: Notebook2