Fix RandomForestClassifier sklearn child metadata

[csadorf]

Fix RandomForestClassifier.as_sklearn() so exported child estimators use sklearn-compatible encoded classes_ and n_classes_ metadata, while the exported forest keeps the original labels.

Adds coverage with non-contiguous classifier labels and compares the exported child estimator metadata against a fitted sklearn random forest.

Contributes to #8180.
Related to #8238.

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📥 Commits

Reviewing files that changed from the base of the PR and between 6ba691f and b1323b7.

📒 Files selected for processing (2)

• python/cuml/cuml/ensemble/randomforestclassifier.py
• python/cuml/tests/test_sklearn_import_export.py

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📝 Walkthrough

Summary by CodeRabbit

• Bug Fixes
  • Improved scikit-learn export for random forest classifiers so the converted model now keeps class metadata consistent at both the model and estimator level.
  • Fixed per-tree class information to better match expected scikit-learn behavior after conversion.
• Tests
  • Added and expanded checks to verify exported random forest classifiers preserve class labels and class counts correctly.

Walkthrough

The PR updates cuML RandomForestClassifier CPU export so estimator-level class metadata is rewritten consistently, and extends sklearn import/export tests to verify top-level and per-estimator class attributes during conversion.

Changes

RandomForestClassifier class metadata

Layer / File(s)	Summary
CPU export class metadata python/cuml/cuml/ensemble/randomforestclassifier.py	RandomForestClassifier._attrs_to_cpu now post-processes exported attrs to update each estimator’s classes_ and n_classes_, and returns matching top-level classes_/n_classes_.
sklearn export tests python/cuml/tests/test_sklearn_import_export.py	The existing round-trip test now checks each exported estimator’s class metadata, and a new as_sklearn() test compares top-level and per-estimator class attributes against scikit-learn.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the main change: fixing sklearn child metadata for RandomForestClassifier.
Description check	✅ Passed	The description matches the code changes and tests around sklearn-compatible child metadata and exported labels.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[jcrist]

Nice fix. One question, but otherwise LGTM.

[csadorf]

/merge