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        "description": "# hd-lib\n\n## Description\nHyperdimensionality computing library for machine learning. This package aims to\ncontain everything needed for training HD models with different settings using\nvarious datasets; there are some included in the package.\n\n## Getting started\n### Prerequisites\nIn order to test the code, please make sure you have python 3 installed and the\npython libraries required:\n```bash\npython3 -m pip install xlsxwriter\npython3 -m pip install sklearn\npython3 -m pip install numpy\npython3 -m pip install tqdm\npython3 -m pip install multiprocess\n```\n### Contributing\nIf you plan on contribute to the project and you are confused, please read the\ndocumentation under ./doc. It describes the code layout and\nrelationships between files and directories. It also contains several examples\non how to use the package.\n\n### Testing\nIf you only plan to test the existing code, make sure you have the following\ndirectories created in the project source:\n```bash\nmkdir ./encoded/\nmkdir ./models/\nmkdir ./out/\nmkdir ./out/ssl/\nmkdir ./out/sup/\nmkdir ./out/recovered/\n```\n\nTo run, depending what is the script you want to run, just do:\n```bash\npython3 src/hd-lib/supervised.py path/to/dataset/dataset_name\npython3 src/hd-lib/semi_supervised.py path/to/dataset/\n```\n\n## About\nPackage started by Alejandro Hern\u00e1ndez Cano. If you are interested in expanding\nthe package but are getting stuck trying to figuring out the code,\nplease feel free to email me any question at ale.hdz333@ciencias.unam.mx\n\n## Acknowledgments\n* Yesong Kim for initial code containing encoding, training, etc, several\n  other resources and feedback\n* Mohsen Imani for initial code for semi-supervised learning and various\n  resources and feedback\n* Tajana Rosing for various resources and feedback\n* All the people at UCSD and other universities that have been working on the\n  theory behind this project, those that have ran tests previously and written\n  code initially\n\n\n",
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