Return Euclidean distances from KMeans transform

[Hashim1999164]

Summary

KMeans.transform currently returns squared distances. sklearn returns Euclidean distances.

This change takes the square root of the transform output so the Python API matches sklearn. score is unchanged.

Fixes #8536

Test plan

Added a regression test against the six point example from the issue.

[copy-pr-bot]

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Enterprise

Run ID: 483e6c34-7f4e-44b2-80a4-a53d1ab2c0dc

📥 Commits

Reviewing files that changed from the base of the PR and between ad513a8 and 4a59652.

📒 Files selected for processing (1)

• python/cuml/cuml_accel_tests/upstream/scikit-learn/xfail-list.yaml

💤 Files with no reviewable changes (1)

• python/cuml/cuml_accel_tests/upstream/scikit-learn/xfail-list.yaml

Included review availability: Your plan provides up to 12 included reviews per hour; 11 remain after this review.

---

📝 Summary

Summary by CodeRabbit

• Bug Fixes

  • KMeans transformations now return Euclidean distances rather than squared-Euclidean distances.
  • Improved consistency with scikit-learn distance results for transformed data.
  • Resolved a discrepancy affecting reported KMeans cluster-center results.

• Tests

  • Added regression coverage validating KMeans distance calculations against explicitly calculated expected values and scikit-learn.
  • Updated compatibility checks to reflect the corrected KMeans behavior.

Walkthrough

KMeans.transform now requests Euclidean distances from the backend. A regression test validates expected values and scikit-learn compatibility. The obsolete xfail entry was removed.

Changes

KMeans distance correction

Layer / File(s)	Summary
Backend distance selection and regression coverage python/cuml/cuml/cluster/kmeans.pyx, python/cuml/tests/test_kmeans.py, python/cuml/cuml_accel_tests/upstream/scikit-learn/xfail-list.yaml	KMeans.transform uses DistanceType.L2SqrtExpanded and returns the backend output unchanged. The regression test compares fixed Euclidean distances with explicit values and scikit-learn. The obsolete xfail entry was removed.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~10 minutes

Severity of issue fixed: Medium

Merge Risk: ⚪ Minimal · up to 4a596

KMeans.transform now returns Euclidean distances compatible with scikit-learn, with regression coverage and the obsolete compatibility exclusion removed. No current merge-blocking risk is identified.

Suggested reviewers: viclafargue

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 3 functions across 1 files.	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 states the primary change: KMeans.transform now returns Euclidean distances.
Description check	✅ Passed	The description accurately explains the squared-distance bug, the scikit-learn compatibility change, the unchanged score behavior, and the added regression test.
Linked Issues check	✅ Passed	The changes satisfy issue #8536 by requesting square-rooted Euclidean distances, adding a regression test against expected values and scikit-learn, and removing the resolved upstream xfail entry.
Out of Scope Changes check	✅ Passed	All changes are directly related to the KMeans.transform distance correction, its regression test, or the corresponding xfail-list update. No unrelated changes are present.

• Fix all pre-merge checks with AI

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

---

_{Comment @coderabbitai help to get the list of available commands.}

[viclafargue]

Thanks for opening a PR!

[viclafargue]

Thanks! LGTM

[viclafargue]

/ok to test ad513a8

[viclafargue]

@Hashim1999164, the sklearn.cluster.tests.test_k_means::test_transform[42-KMeans] test from the Scikit-Learn test suite is now passing with cuml.accel. Could you remove it from the xfail list over there?

[Hashim1999164]

@viclafargue yeah that transform test is passing now so i pulled sklearn.cluster.tests.test_k_means::test_transform[42-KMeans] off the xfail list.