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ONMF-COVID19

Time series applications of onlien NMF on COVID19 data sets
Learns dictionary atoms for short time-evolution patterns of multiple countries or counties, and uses them to predict future values

References

These codes are based on my paper below:

  1. Hanbaek Lyu, Christopher Strohmeier, Deanna Needell, and Georg Menz, “COVID-19 Time Series Prediction by Joint Dictionary Learning and Online NMF” https://arxiv.org/abs/2004.09112

File description

  1. ontf.py : Online Nonnegative Tensor Factorization algorithm (generalization of onmf to the tensor setting by folding/unfolding operation)
  2. time_series_ONMF_COVID19.py : Main file implementing ONMF to COVID-19 time-series data
  3. main.py : Tune hyperparameters and execute main files

Usage

  1. git clone this repository
  2. git clone https://github.com/CSSEGISandData/COVID-19 inside ONMF-COVID19/Data
  3. run main.py

Authors

  • Hanbaek Lyu - Initial work - Website

License

This project is licensed under the MIT License - see the LICENSE.md file for details

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Time series applications of ONMF/ONTF on COVID19 data sets

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