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K-median problem

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This is an old revision of this page, as edited by Michael Hardy (talk | contribs) at 17:34, 23 April 2010 (Distances are always nonnegative, so "absolute values of distances" is redundant.). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

The k-median problem is the problem of finding k centers such that the clusters formed by them are the most compact.

Formally, given a set of data points x, the k centers ci are to be chosen so as to minimize the sum of the distances from each x to the nearest ci.

The problem constitutes a better measure for the k-means clustering algorithm, and is widely used in applications such as facility location[1].

References

  1. ^ http://www.aladdin.cs.cmu.edu/reu/mini_probes/papers/facilitylocation.ppt
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