K-medoids

K-medoids clustering algorithm

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 (R2010b)

[Tu]

Not working for my data as well.
My data was of the dimension 17-by-71.
wanted to find 4 or 6 clusters.
and spread did not work.

[e-mail]

[Graeme]

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

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

[huang]

 

[Mo Chen]

better post your error message

[Dinusha Rathnayaka]

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

[Dinusha Rathnayaka]

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