A new clustering algorithm that identifies clusters step by step is introduced. It is based on the principles of noise clustering dividing the data set into a good cluster and the remaining data that might contain only noise or also other clusters. The algorithm can be applied to finding just a few substructures (clusters), but also as an iterative method to data partition including the identif...
