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