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0.2.1 metats-0.2.1-py3-none-any.whl

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Project: metats
Version: 0.2.1
Filename: metats-0.2.1-py3-none-any.whl
Download: [link]
Size: 16653
MD5: cd87eb75b3858794e834e98dcaa29543
SHA256: db2124dcc6034a3d682469b4106750de926ae1066025dbef3576394cfd0915ce
Uploaded: 2023-03-30 09:33:45 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: metats
Version: 0.2.1
Summary: Meta-Learning for Time Series Forecasting
Author-Email: Sasan Barak <s.barak[at]soton.ac.uk>, Amirabbas Asadi <amir137825[at]gmail.com>, Mohammad Joshaghani <mjoshaghani10[at]gmail.com>
Project-Url: Homepage, https://drsasanbarak.github.io/metats/
License: MIT License Copyright (c) 2021 Amirabbas Asadi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Keywords: timeseries,metalearning,forecasting,unsupervised learning,deeplearning,machine learning
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Dist: torch (>=1.12.1)
Requires-Dist: umap-learn (>=0.5.3)
Requires-Dist: darts (>=0.20.0)
Requires-Dist: lightgbm (>=3.2.1)
Requires-Dist: matplotlib (>=3.4.2)
Requires-Dist: numba (>=0.55.1)
Requires-Dist: numpy (==1.23.5)
Requires-Dist: pandas (>=1.2.4)
Requires-Dist: pbr (>=5.11.1)
Requires-Dist: pdoc (>=12.0.2)
Requires-Dist: scikit-learn (>=1.0.2)
Requires-Dist: scipy (>=1.6.3)
Requires-Dist: seaborn (>=0.11.1)
Requires-Dist: shap (>=0.40.0)
Requires-Dist: sktime (>=0.10.0)
Requires-Dist: tqdm (>=4.60.0)
Requires-Dist: tsfresh (==0.19.0)
Requires-Dist: statsforecast (>=1.5.0)
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pdoc; extra == "dev"
Provides-Extra: dev
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 5363 characters]

WHEEL

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Generator: bdist_wheel (0.40.0)
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Tag: py3-none-any

RECORD

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metats-0.2.1.dist-info/top_level.txt sha256=pwRaWRKVox_qCMonmKq-H0MT48_wPH7ZpTbQL8tM-A8 7
metats-0.2.1.dist-info/RECORD — —

top_level.txt

metats

entry_points.txt

[console_scripts]
metats = metats.__main__:main