Is there a white paper or an article about k-means clustering with CCEA software using "highest reproducibility" approach using different types of starting points? I found the white paper about the ensemble approach and its benefits vs "highest reproducibility" k-means, but am looking for something that would "defend" k-means in general, so to speak, when it's done properly with numeric or attitudinal scale data. Maybe there is an earlier paper, from before Ensemble was added to the software? Maybe even a paper that compares k-means and Latent class clustering and talks about the benefits of each in certain situations, with different types of data, etc.?