Add Hamerly's accelerated K-means algorithm to linfa-clustering#439
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mrsanor wants to merge 2 commits intorust-ml:masterfrom
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Add Hamerly's accelerated K-means algorithm to linfa-clustering#439mrsanor wants to merge 2 commits intorust-ml:masterfrom
mrsanor wants to merge 2 commits intorust-ml:masterfrom
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Implement K-means Hamerly's triangle-inequality optimization as an alternative to Lloyd's algorithm for K-means clustering. 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 - Add KMeansAlgorithm enum (Lloyd | Hamerly) and .algorithm() builder method - Reject Hamerly for incremental fit_with - Comprehensive tests
mrsanor
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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:
Here are the benchmarks between Lloyd and Hamerly