Hierarchical time series forecasting model using Gaussian Processes
Project description
A package that allows you to forecast time series datasets with some type of hierarchical structure. The algorithm is implementedusing PyTorch
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
gpforecaster-0.3.133.tar.gz
(26.9 kB
view details)
Built Distribution
File details
Details for the file gpforecaster-0.3.133.tar.gz
.
File metadata
- Download URL: gpforecaster-0.3.133.tar.gz
- Upload date:
- Size: 26.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 184c085e26eeab0d142dd53b63c0c229fae4567094fa4ea7a649c1754e2a71f0 |
|
MD5 | 8a7f0ada091203a92a1fde9a169ff4d4 |
|
BLAKE2b-256 | 1750bf0240c2be7a23e71a0c02291d3979be26e1ab17158251115c3b388f8c16 |
File details
Details for the file gpforecaster-0.3.133-py3-none-any.whl
.
File metadata
- Download URL: gpforecaster-0.3.133-py3-none-any.whl
- Upload date:
- Size: 34.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 99b979eab51f40f7172acfd69cd9d8e0d5702e0aa65228db669d1b9ca93d12dc |
|
MD5 | 86382ee93805636f2d86b25c30e001de |
|
BLAKE2b-256 | 3e71613edcf03f262f192eb6197435638746bd0a4a8508be5292a29d92cfa0a1 |