On new sequential hard c-medoids
Yukihiro Hamasuna, Yasunori Endo · 2014
This paper presents a new sequential cluster extraction algorithm based on hard c-medoids clustering. The word sequential cluster extraction means that the algorithm extract one cluster at a time. The hard c-medoids is one of the variants of hard c-means clustering. The cluster medoid which is referred to as representative of each cluster is an object in hard c-medoids. The sequential clustering algorithms are based on Dave's noise clustering approach. A characteristic parameter which is called noise parameter is used in noise clustering. We construct a new sequential hard c-medoids algorithm by considering the noise parameter as a variables in optimization problem. First, the optimization problem of new sequential hard c-medoids clustering is introduced. Next, the sequential clustering algorithm is constructed based on the optimization problem. Moreover, the effectiveness of proposed method is shown through numerical experiments.