[ENH] Fix inverted label mapping in OutlierDetectionAdapter & add adapter tests

[Adityakushwaha2006]

Reference Issues/PRs

Fixes #3184
Addresses the request for targeted test coverage for collection anomaly detection adapters.
Fixes a logic error discovered in OutlierDetectionAdapter.

What does this implement/fix? Explain your changes.

This PR adds unit tests for ClassificationAdapter and OutlierDetectionAdapter as requested and fixes a critical logic bug in the outlier adapter.

1. Bug Fix in OutlierDetectionAdapter

• Issue: The previous implementation incorrectly mapped outliers (-1) to 0 (Normal) and inliers (1) to 1 (Anomaly).
• Fix: Updated _predict in aeon/anomaly_detection/collection/_outlier_detection.py to correctly map -1 to 1 (Anomaly).
  • Old Logic: pred[pred == -1] = 0 (Incorrect)
  • New Logic: return (pred == -1).astype(int) (Correct: Outlier becomes Anomaly/True)

2. Added Targeted Tests
Added two new test files focusing exclusively on the adapter "translation" logic (avoiding generic shape/crash tests covered by check_estimator):

• aeon/anomaly_detection/collection/tests/test_outlier_detection.py: Verifies that Sklearn labels (-1, 1) are correctly translated to Aeon standards (1, 0). Includes a safety test to ensure no raw -1 values leak into the output.
• aeon/anomaly_detection/collection/tests/test_classification.py: Verifies that the ClassificationAdapter acts as a transparent passthrough for binary labels.

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

No.

Any other comments?

The tests use DummyClassifier and DummyOutlierDetector mocks to ensure they are fast, deterministic, and do not require training real models.

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[aeon-actions-bot]

Thank you for contributing to aeon

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

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[SebastianSchmidl]

Nice work 👍🏼

Just some minor documentation improvements

[SebastianSchmidl]

LGTM, but let's wait until @MatthewMiddlehurst had a chance to look at this as well. I'm not super sure that we do not already have some dummy fixtures for the tests.

[MatthewMiddlehurst]

Good catch on the output, got the labels backwards!

If you go into the testing module we have some pre-made testing data which can be used here instead of creating it when we don't need to. This is pretty minor though, so can merge without it if no change is made.

[MatthewMiddlehurst]

currently failing tests