Enhanced Data Mining Suite Using Signal Processing

Abstract

Data clustering is an unsupervised data analysis and data mining technique,which offers refined and more abstract views to the inherent structure of a data set by partitioning it into a number of disjoint or overlapping (fuzzy) groups. Hundreds of clustering algorithms and Signal Processing Techniques have been developed by researchers from a number of different scientific disciplines. The intention of this report is to present a special class of clustering algorithms with or without signal processing, namely partition-based methods. After the introduction and a review on iterative relocation clustering algorithms in Data Mining and Signal Processing, some illustrative results are presented.