Adversarial Machine Learning Library (AML)
Computational Economics Research Lab at Washington University in Saint Louis
Game-theoretic adversarial machine learning library providing a set of learner and adversary modules.
Installation
To install the dependencies for adlib do pip install -r requirements.txt. See below for a list of dependencies.
To install adlib, run pip3 install adlib or python3 setup.py install. For development, do python3 setup.py develop.
Dependencies
- Python3
- SciPy
- NumPy
- Matplotlib
- Scikit-learn
- CVXPY (0.4-0.4.11 version)
- Pathos
- Pandas
- Progress
- CVXOPT (optional as a CVXPY solver)
- Jupyter Notebook (optional for notebook demo)
- Py.test (optional for testing)
License
Copyright 2016-2018 Computational Economics Research Lab. Released under the MIT License. See LICENSE for details.
Note
data_reader/data is in .gitignore to speed up git. If you need to make a change from one of those
files, use git add -f $FILE$.