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MNT replace authors and license with standard text (#30511)
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StefanieSenger authored Dec 20, 2024
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3 changes: 2 additions & 1 deletion benchmarks/bench_plot_randomized_svd.py
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A. Szlam et al. 2014
"""

# Author: Giorgio Patrini
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

import gc
import os.path
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4 changes: 0 additions & 4 deletions examples/decomposition/plot_faces_decomposition.py
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matrix decomposition (dimension reduction) methods from the module
:mod:`sklearn.decomposition` (see the documentation chapter
:ref:`decompositions`).
- Authors: Vlad Niculae, Alexandre Gramfort
- License: BSD 3 clause
"""

# Authors: The scikit-learn developers
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3 changes: 0 additions & 3 deletions examples/ensemble/plot_gradient_boosting_early_stopping.py
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applied, can be accessed using the `n_estimators_` attribute. Overall, early
stopping is a valuable tool to strike a balance between model performance and
efficiency in gradient boosting.
License: BSD 3 clause
"""

# Authors: The scikit-learn developers
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6 changes: 0 additions & 6 deletions examples/feature_selection/plot_select_from_model_diabetes.py
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We use the Diabetes dataset, which consists of 10 features collected from 442
diabetes patients.
Authors: `Manoj Kumar <mks542@nyu.edu>`_,
`Maria Telenczuk <https://github.com/maikia>`_, Nicolas Hug.
License: BSD 3 clause
"""

# Authors: The scikit-learn developers
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4 changes: 2 additions & 2 deletions examples/neighbors/plot_caching_nearest_neighbors.py
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Caching nearest neighbors
=========================
This examples demonstrates how to precompute the k nearest neighbors before
This example demonstrates how to precompute the k nearest neighbors before
using them in KNeighborsClassifier. KNeighborsClassifier can compute the
nearest neighbors internally, but precomputing them can have several benefits,
such as finer parameter control, caching for multiple use, or custom
implementations.
Here we use the caching property of pipelines to cache the nearest neighbors
graph between multiple fits of KNeighborsClassifier. The first call is slow
since it computes the neighbors graph, while subsequent call are faster as they
since it computes the neighbors graph, while subsequent calls are faster as they
do not need to recompute the graph. Here the durations are small since the
dataset is small, but the gain can be more substantial when the dataset grows
larger, or when the grid of parameter to search is large.
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3 changes: 2 additions & 1 deletion sklearn/_isotonic.pyx
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# Author: Nelle Varoquaux, Andrew Tulloch, Antony Lee
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# Uses the pool adjacent violators algorithm (PAVA), with the
# enhancement of searching for the longest decreasing subsequence to
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2 changes: 1 addition & 1 deletion sklearn/base.py
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"""HTML representation of estimator.
This is redundant with the logic of `_repr_mimebundle_`. The latter
should be favorted in the long term, `_repr_html_` is only
should be favored in the long term, `_repr_html_` is only
implemented for consumers who do not interpret `_repr_mimbundle_`.
"""
if get_config()["display"] != "diagram":
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4 changes: 0 additions & 4 deletions sklearn/cluster/_agglomerative.py
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These routines perform some hierarchical agglomerative clustering of some
input data.
Authors : Vincent Michel, Bertrand Thirion, Alexandre Gramfort,
Gael Varoquaux
License: BSD 3 clause
"""

# Authors: The scikit-learn developers
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5 changes: 3 additions & 2 deletions sklearn/cluster/_dbscan_inner.pyx
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# Fast inner loop for DBSCAN.
# Author: Lars Buitinck
# License: 3-clause BSD

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from libcpp.vector cimport vector

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8 changes: 3 additions & 5 deletions sklearn/cluster/_hdbscan/_linkage.pyx
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# Minimum spanning tree single linkage implementation for hdbscan
# Authors: Leland McInnes <leland.mcinnes@gmail.com>
# Steve Astels <sastels@gmail.com>
# Meekail Zain <zainmeekail@gmail.com>
# Copyright (c) 2015, Leland McInnes
# All rights reserved.

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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8 changes: 3 additions & 5 deletions sklearn/cluster/_hdbscan/_reachability.pyx
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# mutual reachability distance computations
# Authors: Leland McInnes <leland.mcinnes@gmail.com>
# Meekail Zain <zainmeekail@gmail.com>
# Guillaume Lemaitre <g.lemaitre58@gmail.com>
# Copyright (c) 2015, Leland McInnes
# All rights reserved.

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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6 changes: 3 additions & 3 deletions sklearn/cluster/_hdbscan/_tree.pyx
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# Tree handling (condensing, finding stable clusters) for hdbscan
# Authors: Leland McInnes
# Copyright (c) 2015, Leland McInnes
# All rights reserved.

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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7 changes: 0 additions & 7 deletions sklearn/cluster/_hdbscan/hdbscan.py
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# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# Authors: Leland McInnes <leland.mcinnes@gmail.com>
# Steve Astels <sastels@gmail.com>
# John Healy <jchealy@gmail.com>
# Meekail Zain <zainmeekail@gmail.com>
# 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:

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3 changes: 2 additions & 1 deletion sklearn/cluster/_hierarchical_fast.pyx
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# Author: Gael Varoquaux <gael.varoquaux@normalesup.org>
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

import numpy as np
cimport cython
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5 changes: 2 additions & 3 deletions sklearn/cluster/_k_means_elkan.pyx
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# Author: Andreas Mueller
#
# Licence: BSD 3 clause
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from cython cimport floating
from cython.parallel import prange, parallel
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6 changes: 0 additions & 6 deletions sklearn/cluster/_optics.py
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These routines execute the OPTICS algorithm, and implement various
cluster extraction methods of the ordered list.
Authors: Shane Grigsby <refuge@rocktalus.com>
Adrin Jalali <adrinjalali@gmail.com>
Erich Schubert <erich@debian.org>
Hanmin Qin <qinhanmin2005@sina.com>
License: BSD 3 clause
"""

# Authors: The scikit-learn developers
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3 changes: 2 additions & 1 deletion sklearn/ensemble/_hist_gradient_boosting/_binning.pyx
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# Author: Nicolas Hug
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from cython.parallel import prange
from libc.math cimport isnan
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# Author: Nicolas Hug
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from cython.parallel import prange
import numpy as np
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3 changes: 2 additions & 1 deletion sklearn/ensemble/_hist_gradient_boosting/_predictor.pyx
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# Author: Nicolas Hug
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from cython.parallel import prange
from libc.math cimport isnan
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3 changes: 2 additions & 1 deletion sklearn/ensemble/_hist_gradient_boosting/histogram.pyx
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"""This module contains routines for building histograms."""

# Author: Nicolas Hug
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

cimport cython
from cython.parallel import prange
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4 changes: 3 additions & 1 deletion sklearn/ensemble/_hist_gradient_boosting/splitting.pyx
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- Apply a split to a node, i.e. split the indices of the samples at the node
into the newly created left and right children.
"""
# Author: Nicolas Hug

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

cimport cython
from cython.parallel import prange
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11 changes: 3 additions & 8 deletions sklearn/linear_model/_sag_fast.pyx.tp
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Each class is duplicated for all dtypes (float and double). The keywords
between double braces are substituted during the build.

Authors: Danny Sullivan <dbsullivan23@gmail.com>
Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>
Arthur Mensch <arthur.mensch@m4x.org
Arthur Imbert <arthurimbert05@gmail.com>
Joan Massich <mailsik@gmail.com>

License: BSD 3 clause
"""

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# name_suffix, c_type, np_type
dtypes = [('64', 'double', 'np.float64'),
('32', 'float', 'np.float32')]
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10 changes: 3 additions & 7 deletions sklearn/linear_model/_sgd_fast.pyx.tp
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Each relevant function is duplicated for the dtypes float and double.
The keywords between double braces are substituted during the build.

Authors: Peter Prettenhofer <peter.prettenhofer@gmail.com>
Mathieu Blondel (partial_fit support)
Rob Zinkov (passive-aggressive)
Lars Buitinck

License: BSD 3 clause
"""

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# The dtypes are defined as follows (name_suffix, c_type, np_type)
dtypes = [
("64", "double", "np.float64"),
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6 changes: 3 additions & 3 deletions sklearn/manifold/_barnes_hut_tsne.pyx
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# Author: Christopher Moody <chrisemoody@gmail.com>
# Author: Nick Travers <nickt@squareup.com>
# Implementation by Chris Moody & Nick Travers
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# See http://homepage.tudelft.nl/19j49/t-SNE.html for reference
# implementations and papers describing the technique

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3 changes: 0 additions & 3 deletions sklearn/metrics/_pairwise_distances_reduction/__init__.py
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# Pairwise Distances Reductions
# =============================
#
# Authors: The scikit-learn developers.
# License: BSD 3 clause
#
# Overview
# --------
#
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7 changes: 2 additions & 5 deletions sklearn/neighbors/_binary_tree.pxi.tp
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# KD Tree and Ball Tree
# =====================
#
# Author: Jake Vanderplas <jakevdp@cs.washington.edu>, 2012-2013
# Omar Salman <omar.salman@arbisoft.com>
#
# License: BSD
#
# _binary_tree.pxi is generated and is then literally Cython included in
# ball_tree.pyx and kd_tree.pyx. See ball_tree.pyx.tp and kd_tree.pyx.tp.

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
}}


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4 changes: 2 additions & 2 deletions sklearn/neighbors/_quad_tree.pxd
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# Author: Thomas Moreau <thomas.moreau.2010@gmail.com>
# Author: Olivier Grisel <olivier.grisel@ensta.fr>
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# See quad_tree.pyx for details.

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4 changes: 2 additions & 2 deletions sklearn/neighbors/_quad_tree.pyx
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# Author: Thomas Moreau <thomas.moreau.2010@gmail.com>
# Author: Olivier Grisel <olivier.grisel@ensta.fr>
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause


from cpython cimport Py_INCREF, PyObject, PyTypeObject
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4 changes: 2 additions & 2 deletions sklearn/svm/src/libsvm/libsvm_helper.c
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* but libsvm does not expose this structure, so we define it here
* along some utilities to convert from numpy arrays.
*
* License: BSD 3 clause
* Authors: The scikit-learn developers
* SPDX-License-Identifier: BSD-3-Clause
*
* Author: 2010 Fabian Pedregosa <fabian.pedregosa@inria.fr>
*/


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3 changes: 2 additions & 1 deletion sklearn/utils/_isfinite.pyx
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# Author: John Kirkham, Meekail Zain, Thomas Fan
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from libc.math cimport isnan, isinf
from cython cimport floating
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9 changes: 3 additions & 6 deletions sklearn/utils/_seq_dataset.pyx.tp
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Each class is duplicated for all dtypes (float and double). The keywords
between double braces are substituted during the build.

Author: Peter Prettenhofer <peter.prettenhofer@gmail.com>
Arthur Imbert <arthurimbert05@gmail.com>
Joan Massich <mailsik@gmail.com>

License: BSD 3 clause
"""

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

# name_suffix, c_type, np_type
dtypes = [('64', 'float64_t', 'np.float64'),
('32', 'float32_t', 'np.float32')]
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