Title :
A heuristic method for finding the optimal number of clusters with application in medical data
Author :
Bayati, Hamidreza ; Davoudi, Heydar ; Fatemizadeh, Emad
Author_Institution :
Biological Signal and Image Processing Laboratory (BiSIPL), Department of Electrical Engineering, Sharif University of Technology, Iran
Abstract :
In this paper, a heuristic method for determining the optimal number of clusters is proposed. Four clustering algorithms, namely K-means, Growing Neural Gas, Simulated Annealing based technique, and Fuzzy C-means in conjunction with three well known cluster validity indices, namely Davies-Bouldin index, Calinski-Harabasz index, Maulik-Bandyopadhyay index, in addition to the proposed index are used. Our simulations evaluate capability of mentioned indices in some artificial and medical datasets.
Keywords :
Biomedical imaging; Clustering algorithms; Image processing; Laboratories; Medical simulation; Partitioning algorithms; Scattering; Signal processing; Simulated annealing; cluster validity index; fuzzy c-means; growing neural gas; k-means; simulated annealing; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Simulation; Data Interpretation, Statistical; Fuzzy Logic; Gene Expression Profiling; Humans; Medical Informatics; Models, Genetic; Models, Statistical; Models, Theoretical; Pattern Recognition, Automated;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4650258
