K-means implementation is based on "Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup". While it introduces some overhead and many conditional clauses which are bad for CUDA, it still shows 1.6-2x speedup against the Lloyd algorithm. K-nearest neighbors employ the same triangle inequality idea and require precalculated centroids and cluster assignments, similar to the flattened ball tree.
|Author||Vadim Markovtsev, Charles Determan|
|Date of publication||2017-05-03 15:51:52 UTC|
|Maintainer||Charles Determan <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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