Metadata-Version: 2.1
Name: gpforecaster
Version: 0.3.121
Summary: Hierarchical time series forecasting model using Gaussian Processes
Home-page: UNKNOWN
Author: Luis Roque
Author-email: <roque0luis@gmail.com>
License: UNKNOWN
Keywords: python,time series,hierarchical,forecasting,gaussian process,machine learning
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENCE
Requires-Dist: gpytorch ~=1.9.0
Requires-Dist: numpy ~=1.23.5
Requires-Dist: scikit-learn ~=1.0.1
Requires-Dist: setuptools ~=58.0.4
Requires-Dist: properscoring ~=0.1
Requires-Dist: matplotlib ~=3.3.4
Requires-Dist: tsaugmentation ~=0.5.62
Requires-Dist: psutil ==5.9.3
Requires-Dist: sktime ==0.15.0
Requires-Dist: scikit-optimize ==0.9.0

A package that allows you to forecast time series datasets with some type of hierarchical structure. The algorithm is implementedusing PyTorch

