==== scikit-learn COPYING ====
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==== scikit-learn sklearn/svm/src/liblinear/COPYRIGHT ====

Copyright (c) 2007-2014 The LIBLINEAR Project.
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==== scikit-learn sklearn/externals/array_api_compat/LICENSE ====
MIT License

Copyright (c) 2022 Consortium for Python Data API Standards

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==== scikit-learn sklearn/externals/array_api_extra/LICENSE ====
MIT License

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==== scikit-learn sklearn/svm/src/libsvm/svm.cpp, lines 1-32 ====
/*
Copyright (c) 2000-2009 Chih-Chung Chang and Chih-Jen Lin
All rights reserved.

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*/

==== scikit-learn sklearn/externals/_arff.py, lines 1-25 ====
# =============================================================================
# Federal University of Rio Grande do Sul (UFRGS)
# Connectionist Artificial Intelligence Laboratory (LIAC)
# Renato de Pontes Pereira - rppereira@inf.ufrgs.br
# =============================================================================
# Copyright (c) 2011 Renato de Pontes Pereira, renato.ppontes at gmail dot com
#
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# =============================================================================

==== scikit-learn sklearn/externals/_packaging/version.py, lines 4-26 ====
# Copyright (c) Donald Stufft and individual contributors.
# All rights reserved.

# Redistribution and use in source and binary forms, with or without
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#     1. Redistributions of source code must retain the above copyright notice,
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==== scikit-learn sklearn/externals/_packaging/_structures.py, lines 4-26 ====
# Copyright (c) Donald Stufft and individual contributors.
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==== scikit-learn sklearn/utils/src/MurmurHash3.cpp, lines 2-3 ====
// MurmurHash3 was written by Austin Appleby, and is placed in the public
// domain. The author hereby disclaims copyright to this source code.

==== scikit-learn sklearn/utils/_pprint.py, lines 7-67 ====
# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
# 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 Python Software Foundation;
# All Rights Reserved

# Authors: Fred L. Drake, Jr. <fdrake@acm.org> (built-in CPython pprint module)
#          Nicolas Hug (scikit-learn specific changes)

# License: PSF License version 2 (see below)

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# Brief summary of changes to original code:
# - "compact" parameter is supported for dicts, not just lists or tuples
# - estimators have a custom handler, they're not just treated as objects
# - long sequences (lists, tuples, dict items) with more than N elements are
#   shortened using ellipsis (', ...') at the end.

==== scikit-learn sklearn/utils/_testing.py, lines 575-577 ====
    # The following is derived from pytest, Copyright (c) 2004-2017 Holger
    # Krekel and others, Licensed under MIT License. See
    # https://github.com/pytest-dev/pytest

==== scikit-learn sklearn/cluster/_hdbscan/_tree.pxd, lines 1-28 ====
# Copyright (c) 2015, Leland McInnes
# 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.

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# 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
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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==== scikit-learn sklearn/model_selection/_split.py, lines 1001-1015 ====
        # Implementation is based on this kaggle kernel:
        # https://www.kaggle.com/jakubwasikowski/stratified-group-k-fold-cross-validation
        # and is a subject to Apache 2.0 License. You may obtain a copy of the
        # License at http://www.apache.org/licenses/LICENSE-2.0
        # Changelist:
        # - Refactored function to a class following scikit-learn KFold
        #   interface.
        # - Added heuristic for assigning group to the least populated fold in
        #   cases when all other criteria are equal
        # - Swtch from using python ``Counter`` to ``np.unique`` to get class
        #   distribution
        # - Added scikit-learn checks for input: checking that target is binary
        #   or multiclass, checking passed random state, checking that number
        #   of splits is less than number of members in each class, checking
        #   that least populated class has more members than there are splits.

==== numpydoc, for sklearn/externals/_numpydoc/docscrape.py (numpydoc-894c8c47-LICENSE.txt) ====
Copyright (C) 2008-2023 Stefan van der Walt <stefan@mentat.za.net>, Pauli Virtanen <pav@iki.fi>

Redistribution and use in source and binary forms, with or without
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 1. Redistributions of source code must retain the above copyright
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 2. Redistributions in binary form must reproduce the above copyright
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    the documentation and/or other materials provided with the
    distribution.

THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``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 AUTHOR BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.

==== django, for the slugify adaptation in sklearn/datasets/_base.py (django-1dae4ac1-LICENSE) ====
Copyright (c) Django Software Foundation and individual contributors.
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
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       documentation and/or other materials provided with the distribution.

    3. Neither the name of Django 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 OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

==== pytest, for the derived lines of sklearn/utils/_testing.py (pytest-0d90a31d-LICENSE) ====
The MIT License (MIT)

Copyright (c) 2004 Holger Krekel and others

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
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The above copyright notice and this permission notice shall be included in all
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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.

==== Apache License 2.0, the full text, for sklearn/model_selection/_split.py (wasi-libc-2e6fb9d8-LICENSE-APACHE) ====
                              Apache License
                        Version 2.0, January 2004
                     http://www.apache.org/licenses/

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==== scikit-learn's bundled datasets: their sources and terms ====
scikit-learn 1.9.1 bundles six datasets (sklearn/datasets/data/), each with a description
(sklearn/datasets/descr/), which a loader's DESCR returns and which carries the full citation.
This release packs them unchanged from scikit-learn 1.9.1's copy.

Three are copies of datasets the UCI Machine Learning Repository publishes under the Creative
Commons Attribution 4.0 International licence (CC BY 4.0,
https://creativecommons.org/licenses/by/4.0/):

- Optical Recognition of Handwritten Digits (load_digits, its test set). Creator: E. Alpaydin, as
  descr/digits.rst cites. Source: https://archive.ics.uci.edu/dataset/80. Licence: CC BY 4.0.
  Unchanged from scikit-learn 1.9.1's copy.
- Breast Cancer Wisconsin (Diagnostic) (load_breast_cancer). Creators: W. H. Wolberg, W. N.
  Street, O. L. Mangasarian, as descr/breast_cancer.rst cites. Source:
  https://archive.ics.uci.edu/dataset/17. Licence: CC BY 4.0. Unchanged from scikit-learn 1.9.1's
  copy.
- Wine (load_wine). Original owners: M. Forina et al., PARVUS, as descr/wine_data.rst cites.
  Source: https://archive.ics.uci.edu/dataset/109. Licence: CC BY 4.0. Unchanged from scikit-learn
  1.9.1's copy.

Iris (load_iris) is taken from R. A. Fisher, "The use of multiple measurements in taxonomic
problems", Annual Eugenics 7, Part II, 179-188 (1936), as descr/iris.rst says; UCI's copy
(https://archive.ics.uci.edu/dataset/53, CC BY 4.0) differs from it in two points.

Diabetes (load_diabetes; B. Efron, T. Hastie, I. Johnstone and R. Tibshirani, 2004) and Linnerud
(load_linnerud; M. Tenenhaus, 1998) state no terms.

The two sample photographs of sklearn/datasets/images/ (CC BY 2.0) are not in this release.

