Abstract
Four algorithms for sequential clustering using fuzzy cluster memberships are developed and their effectiveness and efficiency are compared.
First is a known technique of the mountain clustering, and the second is a new method of mountain medoid clustering which uses individuals instead of grid points in the mountain clustering. The third is an algorithm using possibilistic clustering which the authors have developed, and the fourth is an sequential algorithm using the noise clustering with one cluster. In these algorithms, the number of clusters need not be specified beforehand. These four algorithms are described; their performances are discussed and tested using different numerical examples.
