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11 changes: 6 additions & 5 deletions README.md
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·
<a href="docs/leaderboard.md">Leaderboard</a>
·
<a href="docs/experiments.md">Experiments</a>
<a href="docs/evaluation.md">Evaluation</a>
·
<a href="docs/classifiers.md">Classifiers</a>
·
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It brings together datasets, published results, reproducible evaluation workflows, and leaderboard infrastructure in one place. The aim is to make it easier to:

- access benchmark datasets for <a href="docs/datasets.md"> multivariate time series
classification</a>,
- load data into Python workflows,
- explore and compare against <a href="docs/results.md">published results</a>,
- access the <a href="docs/datasets.md"> multiverse </a>, a collection of benchmark
datasets for multivariate time series
classification,
- explore and compare against <a href="docs/results.md">published results</a> of
classification algorithms,
- reproduce baseline <a href="docs/experiments.md"> experiments</a>,
- evaluate <a href="docs/classifiers.md">new classifiers consistently</a>,
- and <a href="docs/contributing.md">contribute</a> new algorithms and results back to
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3 changes: 3 additions & 0 deletions docs/contributing.md
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# Contributing

Coming soon
8 changes: 8 additions & 0 deletions docs/results.md
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## Results for multiverse datasets

Results used in bake offs are available on timeseriesclassification.com and
obtainable in code with aeon.

You can explore and download these results interactively on the COMING SOON website.

Raw spreadsheets are in the results directory.
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