Result of clustering using hard kmeans algorithm with k=3 on a data set of 1000 data samples.

Same as previous  rotated view.

Same as previous  rotated and zoomedin view.

Screenshot of my desktop running the mixturemodels clustering on the same data set as before, searching four clusters. Visible are the visualization GUI, the output on the command line and a display of the entropy of the data distribution over the clusters.

Same results as in the wholescreen shot, data points not displayed. Visible are the cluster center representations and their trajectories.

Display of the entropy of the data distribution over the clusters. For every data point there is a probability distribution over the different clusters. Depicted is the average entropy of these distributions. Needs the RPy module and an installation of R.

Three different points in time of the clustering process. The dynamics of the process become visible. Time point = 20.

Three different points in time of the clustering process. The dynamics of the process become visible. Time point = 29.

Three different points in time of the clustering process. The dynamics of the process become visible. Time point = 35. This was the final step. Convergence was reached in it.
