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''Block Diagram: A simple vector quantizer is shown below''
Huh? Where is it? [[User:Cuddlyable3|Cuddlyable3]] ([[User talk:Cuddlyable3|talk]]) 09:15, 7 June 2011 (UTC)
== Each cluster the same number of points?! ==
"It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them."
This is not true, isn't it?
E.g. clustering a 1-d normally distributioned data with k-means results in groups with very different numbers of points assigned to each cluster.
"Since data points are represented by the index of their closest centroid, commonly occurring data have low error, and rare data high error."
This contradicts the first quote:
If all clusters have the same number of points assigned (As the first quote states), than rarely occuring data is quantized with the same precision as frequently occuring data.
I am confused. I hope i am correct with my concerns here.
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