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* Release 1.4.3 (#855)
* V1.4.2 (#845)
* fixing the release
* pushing to including the .csv
* pre-commit
* v 1.4.2
* Fix `SetRawAnnotations` when no stim channel (#838)
* First try to fix
* Add test
* [pre-commit.ci] auto fixes from pre-commit.com hooks
* Whats new
* enforce desired event ids when creating events from annotations
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Signed-off-by: Pierre Guetschel <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Increase compatibility with Python 3.14 (#848)
* Initial plan
* Increase compatibility with Python 3.14
Co-authored-by: bruAristimunha <[email protected]>
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Co-authored-by: copilot-swe-agent[bot] <[email protected]>
Co-authored-by: bruAristimunha <[email protected]>
* Fix warnings from scikit-learn 1.8+ and introduce FixedPipeline (#850)
* p
* fixing number
* Fix compatibility with scikit-learn 1.8 (#852)
* fixing more colab issues
* updating the utils
* Enhance documentation and update design elements (#853)
* more design details
* more adjust
* more adjusts
* more updates
* updating the readme
* removing the roadmap
* first round
* more modification and almost done
* including subject info
* remove the video
* more details
* updating to colab
* updating the citation
* updating the __init__
* Macro release (#854)
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Signed-off-by: Pierre Guetschel <[email protected]>
Co-authored-by: Bru <[email protected]>
Co-authored-by: Pierre Guetschel <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Copilot <[email protected]>
Co-authored-by: bruAristimunha <[email protected]>
* updating the md and yml
* updating the DNS config
* more documentation fix
* checking links automatically
* Update README.md
Signed-off-by: Bru <[email protected]>
* more fix within the links
* fixing the url
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Signed-off-by: Pierre Guetschel <[email protected]>
Signed-off-by: Bru <[email protected]>
Signed-off-by: Bru <[email protected]>
Co-authored-by: Bruno Aristimunha <[email protected]>
Co-authored-by: Pierre Guetschel <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Copilot <[email protected]>
body: `## Automated Link Check Report\n\nThe weekly link check has detected broken links.\n\n<details>\n<summary>Report</summary>\n\n${report}\n\n</details>`,
For full installation options and troubleshooting, see the docs: https://neurotechx.github.io/moabb/install/install.html
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For full installation options and troubleshooting, see the [documentation](https://moabb.neurotechx.com/docs/install/install.html).
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## Disclaimer
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This project is under the umbrella of [NeuroTechX][link_neurotechx], the international
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community for NeuroTech enthusiasts.
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The Mother of all BCI Benchmarks was founded by [Alexander Barachant](http://alexandre.barachant.org/) and [Vinay Jayaram](https://vinay-jayaram.github.io/).
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The Mother of all BCI Benchmarks was founded by [Alexander Barachant](http://alexandre.barachant.org/) and [Vinay Jayaram][link_vinay].
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It is currently maintained by:
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If you use MOABB in your experiments, please cite MOABB and the related publications:
<pre><code>Aristimunha, B., Carrara, I., Guetschel, P., Sedlar, S., Rodrigues, P., Sosulski, J., Narayanan, D., Bjareholt, E., Barthelemy, Q., Schirrmeister, R. T., Kobler, R., Kalunga, E., Darmet, L., Gregoire, C., Abdul Hussain, A., Gatti, R., Goncharenko, V., Andreev, A., Thielen, J., Moreau, T., Roy, Y., Jayaram, V., Barachant, A., & Chevallier, S. (2025).
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Mother of all BCI Benchmarks (MOABB) (Version 1.4.3). Zenodo. https://doi.org/10.5281/zenodo.10034223</code></pre>
If you use MOABB, remember to <ahref="https://neurotechx.github.io/moabb/cite.html">cite</a>! The largest BCI EEG benchmark is out! Check the <ahref="https://neurotechx.github.io/moabb/paper_results.html">results</a>.
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If you use MOABB, remember to <ahref="https://moabb.neurotechx.com/docs/cite.html">cite</a>! The largest BCI EEG benchmark is out! Check the <ahref="https://moabb.neurotechx.com/docs/paper_results.html">results</a>.
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It is possible to use an external dataset within MOABB as long as it is in Brain Imaging Data Structure (BIDS) format.
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See this `guide <https://bids-specification.readthedocs.io/en/stable/#:~:text=The%20Brain%20Imaging%20Data%20Structure%20(BIDS)%20is%20a%20simple%20and,to%20help%20implement%20the%20standard.>`__ for more information on how to structure your data according to BIDS
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You can use this `class <https://moabb.neurotechx.com/docs/api/generated/moabb.datasets.base.LocalBIDSDataset.html#moabb.datasets.base.LocalBIDSDataset>`__ to convert your local dataset to work within MOABB without creating a new dataset class.
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You can use this `class <https://moabb.neurotechx.com/docs/generated/moabb.datasets.base.LocalBIDSDataset.html>`__ to convert your local dataset to work within MOABB without creating a new dataset class.
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See also `Datasets-Support<https://github.com/NeuroTechX/moabb/wiki/Datasets-Support>`__ for supplementary
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See also the `Wiki<https://github.com/NeuroTechX/moabb/wiki>`__ for supplementary
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detail on datasets (class name, size, licence, etc.)
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===========================
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This guide is intended for users who want to test experimental features or contribute to MOABB’s development. If you only need the stable release, please refer to our
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Visualization of the MOABB datasets, with Motor Imagery (MI) in green, ERP in pink/purple and SSVEP in orange/brown. The size of the circle is proportional to the number of subjects and the contrast depends on the number of electrodes.
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This study conducts an extensive Brain-computer interfaces (BCI) reproducibility analysis on open electroencephalography datasets,
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aiming to assess existing solutions and establish open and reproducible benchmarks for effective comparison within the field. Please note that the results are obtained using `Within-Session evaluation <http://moabb.neurotechx.com/docs/api/generated/moabb.evaluations.WithinSessionEvaluation.html>`_.
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aiming to assess existing solutions and establish open and reproducible benchmarks for effective comparison within the field. Please note that the results are obtained using `Within-Session evaluation <https://moabb.neurotechx.com/docs/generated/moabb.evaluations.WithinSessionEvaluation.html>`_.
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The results are reported regarding mean accuracy and standard deviation across all folds for all sessions and subjects.
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If you use the same evaluation procedure, you should expect similar results if you use the same pipelines and datasets, with some minor variations due to the randomness of the cross-validation procedure.
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