New clustering method uncovers hidden regularities in data

One dataset, one model? This approach does not always produce the most useful insights, as a dataset often contains many different relationships. To better understand them, researchers at the Paluno Research Institute in the Faculty of Computer Science at the University of Duisburg-Essen have developed a method that clusters data according to mathematical functions. The key feature is that neither the number and structure of the functions nor the assignment of data points to them needs to be known in advance.