Double Seasonal Exponential Smoothing using PyTorch + ES-RNN capabilities on top
Double Seasonal Exponential Smoothing using
PyTorch with batched data and multiple series training support.
There are lots of tools built on top of the code in this repository, so the plan is to add them here eventually.
Here's what's published:
- [x] 3d Holt-Winters implementation
- [x] Additive and Multiplicative seasonalities
- [x] Blender module to merge predictions from multiple series.
- [ ] Training loop for normal and bptt training.
- [ ] Uncertainty estimation via sampling.
- [ ] Additional losses
- [ ] RNN training on top of HW.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size torch_es-0.0.1-py3-none-any.whl (10.1 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size torch-es-0.0.1.tar.gz (6.8 kB)||File type Source||Python version None||Upload date||Hashes View|