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Adversarial Machine Learning Library (AML)

Computational Economics Research Lab at Washington University in Saint Louis

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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 $FILE$.

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Game-Theoretic Adversarial Machine Learning Library

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