Metadata-Version: 2.1
Name: tsml-eval
Version: 0.0.1
Summary: A package for benchmarking time series machine learning tools.
Author-email: Matthew Middlehurst <m.middlehurst@uea.ac.uk>, Tony Bagnall <ajb@uea.ac.uk>
License: BSD 3-Clause License
        
        Copyright (c) 2022, The Time Series Machine Learning (tsml) developers.
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        1. Redistributions of source code must retain the above copyright notice, this
           list of conditions and the following disclaimer.
        
        2. Redistributions in binary form must reproduce the above copyright notice,
           this list of conditions and the following disclaimer in the documentation
           and/or other materials provided with the distribution.
        
        3. Neither the name of the copyright holder nor the names of its
           contributors may be used to endorse or promote products derived from
           this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
        DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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Project-URL: homepage, https://www.timeseriesclassification.com/
Project-URL: repository, https://github.com/time-series-machine-learning/tsml-estimator-evaluation/
Keywords: data-science,machine-learning,data-mining,time-series,classification,regression,clustering
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Requires-Python: <3.11,>=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: sktime (>=0.14.0)
Requires-Dist: convst
Requires-Dist: wildboar
Requires-Dist: stumpy
Requires-Dist: networkx
Requires-Dist: requests
Requires-Dist: torch
Provides-Extra: dev
Requires-Dist: pre-commit ; extra == 'dev'
Requires-Dist: pytest ; extra == 'dev'
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-design ; extra == 'docs'
Requires-Dist: sphinx-gallery ; extra == 'docs'
Requires-Dist: numpydoc ; extra == 'docs'
Requires-Dist: nbsphinx ; extra == 'docs'
Requires-Dist: furo ; extra == 'docs'

# tsml-eval

Evaluation tools for classification, regression and clustering algorithms built on the sktime interface.

Dependency installation
-----------------------

pip install -r requirements.txt

Export package versions to new requirements
-------------------------------------------

pip freeze > requirements.txt


sktime install from main, branch or fork
----------------------------------------

You can use this package with a sktime install that isn't deployed to pypip.

- First uninstall current sktime: 'pip uninstall sktime'
- Then install from git using i.e.
  - pip install git+https://github.com/sktime/sktime.git@main
  - pip install git+https://github.com/sktime/sktime.git@uea_debugging
  - pip install git+https://github.com/MatthewMiddlehurst/sktime-mm.git@main
