Update dependency scikit-learn to ~1.4.0

[renovate-bot]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
scikit-learn (source)	~1.0 -> ~1.4.0

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Release Notes

scikit-learn/scikit-learn (scikit-learn)

v1.4.0

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v1.3.2: Scikit-learn 1.3.2

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We're happy to announce the 1.3.2 release.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.3.html#version-1-3-2

This version supports Python versions 3.8 to 3.12.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

v1.3.1: Scikit-learn 1.3.1

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We're happy to announce the 1.3.1 release.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.3.html#version-1-3-1

This version supports Python versions 3.8 to 3.12.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

v1.3.0: Scikit-learn 1.3.0

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We're happy to announce the 1.3.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights\_1\_3\_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.3.html

This version supports Python versions 3.8 to 3.11.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

v1.2.2: Scikit-learn 1.2.2

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We're happy to announce the 1.2.2 release.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.2.html#version-1-2-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

v1.2.1: scikit-learn 1.2.1

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We're happy to announce the 1.2.1 release.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.2.html#version-1-2-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

v1.2.0: Scikit-learn 1.2.0

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We're happy to announce the 1.2.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights\_1\_2\_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.2.html

This version supports Python versions 3.8 to 3.11.

v1.1.3: scikit-learn 1.1.3

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We're happy to announce the 1.1.3 release.

This bugfix release only includes fixes for compatibility with the latest SciPy release >= 1.9.2 and wheels for Python 3.11. Note that support for 32-bit Python on Windows has been dropped in this release. This is due to the fact that SciPy 1.9.2 also dropped the support for that platform. Windows users are advised to install the 64-bit version of Python instead.

You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.1.html#version-1-1-3

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

v1.1.2: scikit-learn 1.1.2

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We're happy to announce the 1.1.2 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.1.html#version-1-1-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

v1.1.1: scikit-learn 1.1.1

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We're happy to announce the 1.1.1 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.1.html#version-1-1-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

v1.1.0: scikit-learn 1.1.0

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We're happy to announce the 1.1.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights\_1\_1\_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.1.html#changes-1-1

This version supports Python versions 3.8 to 3.10.

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Configuration

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⚠ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

♻ Renovate will retry this branch, including artifacts, only when one of the following happens:

• any of the package files in this branch needs updating, or
• the branch becomes conflicted, or
• you click the rebase/retry checkbox if found above, or
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The artifact failure details are included below:

File name: poetry.lock

Creating virtualenv cloud-datasets-02SzFaNK-py3.8 in /home/ubuntu/.cache/pypoetry/virtualenvs
Updating dependencies
Resolving dependencies...


The current project's Python requirement (3.8.12) is not compatible with some of the required packages Python requirement:
  - scikit-learn requires Python >=3.9, so it will not be satisfied for Python 3.8.12

Because scikit-learn (1.4.0) requires Python >=3.9
 and no versions of scikit-learn match >1.4.0,<1.5.0, scikit-learn is forbidden.
So, because cloud-datasets depends on scikit-learn (~1.4.0), version solving failed.

  • Check your dependencies Python requirement: The Python requirement can be specified via the `python` or `markers` properties
    
    For scikit-learn, a possible solution would be to set the `python` property to "<empty>"

    https://python-poetry.org/docs/dependency-specification/#python-restricted-dependencies,
    https://python-poetry.org/docs/dependency-specification/#using-environment-markers