Add Hamerly's accelerated K-means algorithm to linfa-clustering

[mrsanor]

Implement K-means Hamerly's triangle-inequality optimization as an alternative to Lloyd's algorithm for K-means clustering for speed optimization. For each observation the algorithm maintains upper/lower distance bounds and skips centroid comparisons that cannot change the assignment, yielding the same results as Lloyd but with significantly fewer distance computations when clusters are well separated.

Key changes:

• The new Hamerly K-means algorithm (uses the same m_k-means for centroid calculations as Lloyd)
• Add KMeansAlgorithm enum (Lloyd | Hamerly) and .algorithm() builder method
• Reject Hamerly for incremental fit_with
• Comprehensive tests

Here are the benchmarks between Lloyd and Hamerly

[relf]

Thanks for this contribution which looks good to me. Could you also rebase your PR on the current master? (some new lints have been fixed)

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 77.54%. Comparing base (8167a62) to head (617383d).

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #439      +/-   ##
==========================================
+ Coverage   76.98%   77.54%   +0.55%     
==========================================
  Files         106      106              
  Lines        7405     7579     +174     
==========================================
+ Hits         5701     5877     +176     
+ Misses       1704     1702       -2     

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[mrsanor]

Here is new report after the benchmark order change