[ENH] Adds RED CoMETS classifier

[zy18811]

PR adding RED CoMETS classifier.

Not sure what algorithm type it falls under? So have put into hybrid for now.

Adds a soft dependency to imbalanced-learn.

TODO

• Speed up SAX transforms using parallelisation
• Fix some minor formatting issues
• Add tests
• Add examples in docstrings + update docs/api_reference
• get_test_params()

PR checklist

• I've added myself to the list of contributors.
• Optionally, I've updated aeon's CODEOWNERS to receive notifications about future changes to these files.
• The PR title starts with either [ENH], [MNT], [DOC], or [BUG] indicating whether the PR topic is related to enhancement, maintenance, documentation, or bug.
• For new estimators, I've added the estimator to the online documentation.

[TonyBagnall]

great, thanks Luca. The categories are necessarily fluid, but I would probably put it in dictionary based?

[TonyBagnall]

also, would you like to join our slack @zy18811 https://join.slack.com/t/aeon-toolkit/shared_invite/zt-2466yn6zm-5fV0EW8JjSVUoe2hzJjRMw

[TonyBagnall]

could you add some testing code for this? You can use skip test for the soft dependency, for example, someting like this before each test function

@pytest.mark.skipif(
    not _check_soft_dependencies("imblearn", severity="none"),
    reason="skip test if required soft dependency esig not available",
)

[TonyBagnall]

couple of very minor docstring comments, but otherwise this looks great, thank you for the contribution

[TonyBagnall]

this test failure is nothing to do with your PR, just a weird tensorflow thing

[zy18811]

Think I've addressed the two docstring issues :) 🚀

[TonyBagnall]

one more tiny thing on the soft dependencies and I think its ready, great job

[TonyBagnall]

LGTM

[MatthewMiddlehurst]

Hi Luca, thanks for the contribution. Great work.

One minor change to the all-contributors file would be good, I can monitor and merge after that is complete unless anyone else wants to review and request changes.