K-median problem: Difference between revisions
Appearance
Content deleted Content added
No edit summary |
No edit summary |
||
Line 1: | Line 1: | ||
{{DISPLAYTITLE |
{{DISPLAYTITLE:''k''-median problem}} |
||
The '''''k''-median problem''' is the problem of finding ''k'' centers such that the clusters formed by them are the most compact. |
The '''''k''-median problem''' is the problem of finding ''k'' centers such that the clusters formed by them are the most compact. |
Revision as of 17:41, 23 April 2010
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].