My problem is that it is difficult to get the optimal cluster number by using k-means, so I thought of using a hierarchical algorithm to find the optimal cluster number. After defining my ideal classification I want to use this classification to find the centroids with k-means, without iteration.
data= rand(300,5);
D = pdist(data);
Z = linkage(D,'ward');
T = cluster(Z,'maxclust',6);
Now I want to use the clusters defined in vector T
and the positions in to k-means algorithm without iterations. Can anyone give a tip how to do?
Thank you.