fedfs
Federated Feature Selection as in the paper https://arxiv.org/abs/2109.11323
Science Score: 36.0%
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○Scientific vocabulary similarity
Low similarity (5.6%) to scientific vocabulary
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Repository
Federated Feature Selection as in the paper https://arxiv.org/abs/2109.11323
Basic Info
Statistics
- Stars: 5
- Watchers: 1
- Forks: 2
- Open Issues: 3
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Metadata Files
README.md
FedFS
Federated Feature Selection as in the paper https://arxiv.org/abs/2109.11323
If used in scientific publication, please cite the method and library as follows:
@misc{cgv2021federated, title={Federated Feature Selection for Cyber-Physical Systems of Systems}, author={Pietro Cassar and Alberto Gotta and Lorenzo Valerio}, year={2021}, eprint={2109.11323}, archivePrefix={arXiv}, primaryClass={cs.LG} }
Requirements
Python>=3.6
Use the "requirements.txt" file to install all the necessary libraries.
Important: This library exploits methods from pyMIToolbox (https://github.com/tud-zih-energy/pymit). Please, be sure to install it in the python environment before running the code.
Owner
- Name: Lorenzo
- Login: ranyus
- Kind: user
- Location: Pisa, Italy
- Company: IIT-CNR
- Website: https://www.iit.cnr.it/en/lorenzo.valerio
- Twitter: l0r3nz0val3r10
- Repositories: 1
- Profile: https://github.com/ranyus
I'm a researcher at the National Research Council of Italy, I'm a computer scientist and I'm interested in the combination of ML with distributed systems.
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Dependencies
- numpy *
- pandas *
- scikit-learn *
- scipy *