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RPyCA

This repository is currently being developed.

As files for the data sets being used are too large to host on Github, they can be downloaded at the links below.

Main data set:

https://www.unb.ca/cic/datasets/ids-2017.html

Secondary data set (LLDOS 2.0.2 - Scenario Two):

https://www.ll.mit.edu/r-d/datasets/2000-darpa-intrusion-detection-scenario-specific-datasets

This started as a research project of investigating whether Robust PCA can be used to improve the performance of neural networks. Currently, it is being developed to become a Python package for further application. Once completed, users will be able to import the package into a python file, and run the commands to enhance their dataset(s). Output will include training, testing, and validation sets along with their corresponding sets for labels.

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