Cross threshold when choosing components pca

[larsevj]

Highlights one issue with using PCA to decide the number of clusters to use. If you have say 20 observations, where 19 of them are highly correlated and the last observation is independent of the others, then 1 principal component which is a linear combination of these 19 might be enough to explain more than 95% of the variance, and the algorithm would then decide on 1 cluster.

• PR title captures the intent of the changes, and is fitting for release notes.
• Added appropriate release note label
• Commit history is consistent and clean, in line with the contribution guidelines.
• Make sure unit tests pass locally after every commit (git rebase -i main --exec 'pytest tests/ert/unit_tests tests/everest -n auto --hypothesis-profile=fast -m "not integration_test"')

When applicable

• When there are user facing changes: Updated documentation
• New behavior or changes to existing untested code: Ensured that unit tests are added (See Ground Rules).
• Large PR: Prepare changes in small commits for more convenient review
• Bug fix: Add regression test for the bug
• Bug fix: Create Backport PR to latest release

[codspeed-hq]

CodSpeed Performance Report

Merging #9874 will improve performances by 13.41%

_{Comparing larsevj:cross_threshold_when_choosing_components_pca (4a0ea64) with main (6ba3112)}

Summary

⚡ 1 improvements
✅ 24 untouched benchmarks

Benchmarks breakdown

	Benchmark	BASE	HEAD	Change
⚡	test_direct_dark_performance_with_storage[gen_x: 20, sum_x: 20 reals: 10-summary-get_record_observations]	1.5 ms	1.4 ms	+13.41%