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AdversariaLib is a general-purpose library for the automatic evaluation of machine learning-based classifiers under adversarial attacks. It comes with a set of powerful features: **Easy-to-use**: Running sophisticated experiments is as easy as launch a single script. **Wide range of supported ML algorithms** All supervised learning algorithms supported by scikit-learn, as well as Artificial Neural Networks (ANNs) **Fast Learning and Evaluation** Thanks to scikit-learn and FANN, all supported ML algorithms are optimized and written in C/C++ language. **Built-in attack algorithms** Gradient Descent Attack **Extensible** Other attack algorithms can be easily added to the library. **Multi-processing** Do you want to further save time? The built-in attack algorithms can run concurrently on multiple processors.
Last, but not least, AdversariaLib is **free software**, released under the GNU General Public License version 3!

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