Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...