[ENH] Implemented COPOD for anomaly detection

[notaryanramani]

Reference Issues/PRs

Fixes #2111

What does this implement/fix? Explain your changes.

Implements COPOD from PyOD to be used in aeon framework along with some test cases.

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

No

Any other comments?

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I have added the following labels to this PR based on the title: [ $\color{#FEF1BE}{\textsf{enhancement}}$ ].
I have added the following labels to this PR based on the changes made: [ $\color{#6F6E8D}{\textsf{anomaly detection}}$ ]. Feel free to change these if they do not properly represent the PR.

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[SebastianSchmidl]

Well done. Thank you again!
I still think that the tests are excessive because we already test all cases with the PyODAdapter. Could you boil it down to a couple of tests specific for the COPOD-estimator? In addition, the current tests still refer to iforest 😉

[notaryanramani]

@CodeLionX I am not familiar with COPOD algorithm. Could you please give an idea what kind of tests are required?

[SebastianSchmidl]

@CodeLionX I am not familiar with COPOD algorithm. Could you please give an idea what kind of tests are required?

I trust that the implementation in PyOD is correct. So, our tests would check that we integrate it in aeon correctly:

• instantiating the class should work (when pyod is installed): you can just keep one of the end-to-end tests
• the parameters of the algorithm should be correctly passed down to the PyOD model
• aeon with window_size=1 and stride=1 should produce the same results as calling the PyOD model directly, when I am not mistaken

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[notaryanramani]

Umm... sorry I was trying to rebase the branch and something wild happened 😅. Should I close this PR and open a new one?

[SebastianSchmidl]

Looks good. Just some minor changes so that we don't need to clean it up later 👍🏼

[TonyBagnall]

great, thanks for this