Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
Abstract. A fuzzy c-means algorithm incorporating the notion of dominant colors and spatial homogeneity is proposed for the color clustering problem. The proposed algorithm extract...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
— Data mining in biological structure libraries can be a powerful tool to better understand biochemical processes. This article introduces the LISA algorithm which enables the re...