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Add example notebook for using aeon distances with sklearn clusterers #2511

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SalmanDeveloperz
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Reference Issues/PRs

Fixes #1241

What does this implement/fix? Explain your changes.

This pull request introduces a new Jupyter Notebook: sklearn_clustering_with_aeon_distances.ipynb. The notebook demonstrates how to integrate aeon's distance metrics with scikit-learn clustering algorithms. It includes:

Hierarchical Clustering: Using AgglomerativeClustering with metric="precomputed".
Density-Based Clustering: Using DBSCAN and OPTICS with metric="precomputed".
Spectral Clustering: Using SpectralClustering with affinity="precomputed" and the inverse of the distance matrix as the similarity matrix.
This addition enhances the clustering documentation, showing how to combine aeon’s distance metrics with widely-used scikit-learn clusterers.

Does your contribution introduce a new dependency? If yes, which one?

No new dependencies introduced.

Any other comments?

  • The notebook has been tested locally, and all cells execute without errors.

  • A reference to this notebook has been added to the clustering section of the documentation.

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@aeon-actions-bot aeon-actions-bot bot added the examples Example notebook related label Jan 22, 2025
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I have added the following labels to this PR based on the changes made: [ $\color{#45FD64}{\textsf{examples}}$ ]. Feel free to change these if they do not properly represent the PR.

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@SalmanDeveloperz
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Dear maintainers,
I have created a new notebook and would like to know where to add its reference in the following documentation:

Clustering Overview
Clustering with sklearn.cluster
Could you please guide me on the most appropriate sections in these files to include the reference to the new notebook? I want to ensure it integrates well with the existing content before committing the changes.
Looking forward to your advice.
Best Regards

@TonyBagnall
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Dear maintainers, I have created a new notebook and would like to know where to add its reference in the following documentation:

Clustering Overview Clustering with sklearn.cluster Could you please guide me on the most appropriate sections in these files to include the reference to the new notebook? I want to ensure it integrates well with the existing content before committing the changes. Looking forward to your advice. Best Regards

hi, thanks for this, we will take a look

@SebastianSchmidl SebastianSchmidl added documentation Improvements or additions to documentation clustering Clustering package distances Distances package labels Jan 25, 2025
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Dear maintainers, I have created a new notebook and would like to know where to add its reference in the following documentation:

Clustering Overview Clustering with sklearn.cluster Could you please guide me on the most appropriate sections in these files to include the reference to the new notebook? I want to ensure it integrates well with the existing content before committing the changes. Looking forward to your advice. Best Regards

Please refer to the links in my comment of the corresponding issue.

@SalmanDeveloperz
Resolved conflicts and updated notebook:
714be28 
- Removed "metric=..." details from TOC and introduction.
- Renamed "Loading Data" to "Example Dataset."
- Deleted redundant Introduction section.
@SalmanDeveloperz
Simplified dataset loading using load_unit_test(split="train") as s…
fd26c31 
…uggested.
@SalmanDeveloperz
Added this sentence after the introductory line:
450b0cc 
"For a comprehensive overview of all available distance metrics in aeon, see the aeon distances API reference."
@SalmanDeveloperz
Changes made:-
49d8e66 
"AgglomerativeClustering is, as the name suggests, an agglomerative approach that works by merging clusters bottom-up."
Clarified Supported Linkage Methods:

Included the supported linkage methods (single, complete, average, weighted) for precomputed distance matrices.
@SalmanDeveloperz
Added links to the scikit-learn documentation pages for all reference…
1ce463e 
…d estimators.
@SalmanDeveloperz
Updated distance-to-similarity conversion to normalize distances and …
fb04db0 
…subtract from 1, ensuring proper preservation of distance distribution.
@SalmanDeveloperz
Removed the references section as it was not cited in the notebook, p…
0c3435b 
…er feedback.
@SalmanDeveloperz
Added a reference to the new notebook (sklearn_clustering_with_aeon_d…
b033484 
…istances.ipynb) in the Clustering Overview under Clustering Notebooks.
@SalmanDeveloperz
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Please refer to the links in my comment of the corresponding issue.

Thank you for the guidance! I have added a reference in the clustering.ipynb notebook under the Clustering Notebooks section, as suggested.

Please let me know if there are additional updates or adjustments required!

@MatthewMiddlehurst
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this is failing the tests currently, please click on details to see why and resolve.

@SebastianSchmidl
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Could you add a link to your new notebook from the Clustering-with-sklearn.cluster section of the distances/sklearn_distances-notebook, too?

@SalmanDeveloperz
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Could you add a link to your new notebook from the Clustering-with-sklearn.cluster section of the distances/sklearn_distances-notebook, too?

Inserted the required reference in the Clustering-with-sklearn.cluster section of sklearn_distances.ipynb. Please advise if any further refinements are necessary.

@SebastianSchmidl
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I think, we also miss a link to this notebook from https://aeon-toolkit--2511.org.readthedocs.build/en/2511/examples.html#clustering

@SalmanDeveloperz
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Added the missing link to the new notebook in the Clustering section of examples.md. Please let me know if any further changes are needed!

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@chrisholder chrisholder Awaiting requested review from chrisholder

@TonyBagnall TonyBagnall Awaiting requested review from TonyBagnall

@SebastianSchmidl SebastianSchmidl Awaiting requested review from SebastianSchmidl

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clustering Clustering package distances Distances package documentation Improvements or additions to documentation examples Example notebook related
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[DOC] Hierarchical, spectral, or density-based clustering using sklearn and aeon distance metrics
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@SalmanDeveloperz @TonyBagnall @SebastianSchmidl @MatthewMiddlehurst