Hi admins,

My team is working on optimization on scikit-learn staff now. When it comes to 
kmeans, I find there are two algorithms, one of which is lloyd and the other is 
elkan, which is the optimized one for lloyd using triangle inequality.  In the 
older version of scikit-learn, elkan only supports dense dataset instead of 
sparse one. And in the latest version, elkan supports both type of datasets. So 
there is a question why both two algorithms are kept in kmeans since they do 
the almost same thing and elkan is a optimized one for lloyd. Are there any 
precision difference between two algorithms and how can I decide what algorithm 
to use?

Best regards,
George Fan
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