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K-medoids

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K-medoids

by Mo Chen

 

30 Sep 2010 (Updated 15 Feb 2012)

K-medoids clustering algorithm

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Description

Efficient implementation of K-medoids clustering methods. This method is similar to K-means but more robust.
For more detail, please see
http://en.wikipedia.org/wiki/K-medoids

It is usually more robust than kmeans algorithm.

Input data are assumed column vectors.

try
load data;
label=kmedoids(x,3);
spread(x,label);

MATLAB release MATLAB 7.11 (2010b)
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Comments and Ratings (5)
18 Mar 2012 Dinusha Rathnayaka

SIMPLY NOT working.
load data;
label=kmedoids(x,3);
spread(x,label);.

18 Mar 2012 Dinusha Rathnayaka

Dear Sir Pls help!!! My Matlab version is Matlab7.6.0..Is this the reason?
Pls reply when you free!!!

20 Mar 2012 Mo Chen

better post your error message

09 Apr 2012 huang  
24 May 2012 Graeme

Undefined function 'randsample' for input arguments of type 'double'.

Error in kmedoids (line 8)
[~, label] = min(D(randsample(n,k),:));

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Updates
04 Feb 2012

significantly simplify the code

15 Feb 2012

correct description

Tag Activity for this File
Tag Applied By Date/Time
clustering Mo Chen 30 Sep 2010 13:29:45
kmedoids Mo Chen 30 Sep 2010 13:29:45
kmeans Mo Chen 30 Sep 2010 13:29:45
clustering Shoaib 10 Jan 2011 02:14:46
clustering huang 09 Apr 2012 13:28:09

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