Hello all, I am using k-means to cluster some data and I have the following two questions:
1. In a Cluster what is the difference of the centre and the centroid in the specific implementation? I was trying to grasp the convergence condition by looking at the code and I saw that the distance between the centre and the centroid is calculated. I think I understand what the centroid is but what is the centre then? 2. Why the k-means results have 2 final clusters? I compared the results with R kmeans and it seems that the later final cluster is the right one. But what is the first one then? Sorry if this information is somewhere available but I couldn't find it so far. Any help will be much appreciated. Aspasia
