[ENH] Add load_classification_encoded wrapper for label encoding

[satwiksps]

[ENH] Add load_classification_encoded wrapper for label encoding

Reference Issue

• Fixes [ENH] Add a label encoder option when loading dataset #2807.

What does this implement/fix? Explain your changes.

This PR implements a new wrapper function, load_classification_encoded, in aeon/datasets/_data_loaders.py.

As discussed in issue #2807, this function allows users to load classification datasets with target labels automatically encoded as integers (using sklearn.LabelEncoder) without modifying the signature of the base load_classification function.

Key changes:

1. New Function: Added load_classification_encoded. It loads train/test splits, fits a label encoder on the training set, transforms both sets, and optionally returns the fitted encoder.
2. Export: Exposed the function in aeon/datasets/__init__.py.
3. Testing: Added a unit test in aeon/datasets/tests/test_data_loaders.py to verify integer conversion and encoder return behavior.

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

No

Any other comments?

I chose to implement this as a separate wrapper function rather than modifying load_classification arguments to avoid complicating the existing API signature, consistent with the maintainers' suggestions in the issue thread.

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I have added the following labels to this PR based on the title: [ enhancement ].
I have added the following labels to this PR based on the changes made: [ datasets ]. Feel free to change these if they do not properly represent the PR.

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