🔬 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:

@misc{dai2021significance,
      title={Significance tests of feature relevance for a blackbox learner},
      author={Ben Dai and Xiaotong Shen and Wei Pan},
      year={2021},
      eprint={2103.04985},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}

Notebook

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