Title :
Smart: Novel self splitting-merging clustering algorithm
Author :
Fa, Rui ; Nandi, Asoke K.
Author_Institution :
Dept. of Electr. Eng. & Electron., Univ. of Liverpool, Liverpool, UK
Abstract :
In this paper, we propose a new self splitting-merging clustering algorithm, named splitting-merging awareness tactics (SMART). The novel framework, which integrates many techniques, starts with one cluster and employs a splitting-while-merging process. The SMART has self-awareness to split and merge the clusters automatically in iterations. Both the framework and the techniques are detailed and illustrated by a good benchmark test. Furthermore, three microarray gene expression datasets are studied using our approach. The numerical results show that our proposal is automotive and effective.
Keywords :
pattern clustering; SMART; automotive; microarray gene expression datasets; self splitting-merging clustering algorithm; splitting-merging awareness tactics; Algorithm design and analysis; Benchmark testing; Clustering algorithms; Gene expression; Merging; Partitioning algorithms; Signal processing algorithms; microarray; self splitting-merging clustering algorithm;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
Conference_Location :
Bucharest
Print_ISBN :
978-1-4673-1068-0