DocumentCode :
3563707
Title :
On new sequential hard c-medoids
Author :
Hamasuna, Yukihiro ; Endo, Yasunori
Author_Institution :
Dept. of Inf., Kinki Univ., Higashi-Osaka, Japan
fYear :
2014
Firstpage :
489
Lastpage :
494
Abstract :
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.
Keywords :
optimisation; pattern clustering; Dave noise clustering approach; characteristic parameter; cluster representation; noise parameter; optimization problem; sequential cluster extraction algorithm; sequential clustering algorithm; sequential hard c-medoid clustering; word sequential cluster extraction; Clustering algorithms; Clustering methods; Kernel; Linear programming; Noise; Optimization; Partitioning algorithms; hard c-medoids; noise parameter; sequential cluster extraction; sequential hard c-medoids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
Type :
conf
DOI :
10.1109/SCIS-ISIS.2014.7044687
Filename :
7044687
Link To Document :
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