The KDD process aims at the discovery and extraction of “useful” knowledge (such as interesting patterns, classification, rules etc) from large data repositories. A widely rec...
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...
We introduce two appearance-based methods for clustering a set of images of 3-D objects, acquired under varying illumination conditions, into disjoint subsets corresponding to ind...
This paper proposes a novel data clustering algorithm, coined ‘cellular ants’, which combines principles of cellular automata and ant colony optimization algorithms to group s...