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...
Abstract--This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzz...
Clustering for the analysis of the gene expression profiles has been used for identifying the functions of the genes and of unknown genes. Since the genes usually belong to multipl...
In this paper, we present a local, adaptive optimization scheme for adjusting the number of clusters in fuzzy C-means clustering. This method is especially motivated by online app...
— This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters ...