Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k-medoids algorithm and the Girvan...
Recent digital signal processors (DSPs) show a homogeneous VLIW-like data path architecture, which allows C compilers to generate efficient code. However, still some special rest...
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Abstract. Feature extraction based on evolutionary search offers new possibilities for improving classification accuracy and reducing measurement complexity in many data mining and...