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
These codes are based on my paper below:
- 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
- ontf.py : Online Nonnegative Tensor Factorization algorithm (generalization of onmf to the tensor setting by folding/unfolding operation)
- time_series_ONMF_COVID19.py : Main file implementing ONMF to COVID-19 time-series data
- main.py : Tune hyperparameters and execute main files
- git clone this repository
- git clone https://github.com/CSSEGISandData/COVID-19 inside ONMF-COVID19/Data
- run main.py
- Hanbaek Lyu - Initial work - Website
This project is licensed under the MIT License - see the LICENSE.md file for details