This is a PyTorch and TensorLy implementation of Time-Aware Tensor Decomposition for Sparse Tensors.
- Python 3.6+
- NumPy
- pandas
- scikit-learn
- PyTorch
- TensorLy
- Install all of the prerequisites
- You can run the demo script by
bash demo.sh, which simply runssrc/main.py. - You can change the datasets and hyper-parameters by modifying
src/main.py. - you can check out the running results in
outdirectory.
Preprocessed datasets are in the data directory.
| Name | Description | Size | NNZ | Granularity in Time | Original Source |
|---|---|---|---|---|---|
| Beijing Air Quality | time x locations x pollutants | 35064 x 12 x 6 | 2454305 | hourly | Link |
| Madrid Air Quality | time x locations x pollutants | 2678 x 26 x 17 | 337759 | daily | Link |
| Radar Traffic | time x locations x directions | 17937 x 17 x 5 | 495685 | hourly | Link |
| Indoor Condition | time x locations x sensor | 19735 x 9 x 2 | 241201 | every 10 minutes | Link |
| Server Room | time x air conditioning x server power x locations | 4157 x 3 x 3 x 34 | 1009426 | 1 second | Link |