Cluster generatorsData clustering is an unsupervised classification technique. Its aim is to identify groups of similar data items within large data sets. The output of a clustering algorithm is typically a partitioning of a data set, such that data items within the same cluster are similar and those within different cluster are dissimilar. Clustering problems are encountered in many different disciplines, and the performance of a given clustering algorithm usually varies for different types of data.
Synthetic data sets, in which the properties of the clusters
and the correct cluster assignments are