Shah, Jehan Zeb and Salim, Naomie (2005) Fuzzy clustering algorithms and their applications to chemical datasets. In: Postgraduate Annual Research Seminar 2005.
In this work the importance of fuzzy based clustering methods is highlighted and their applications in the field of chemoinformatics, and issues involved are reviewed. The various methods and approaches of fuzzy clustering are outlined. The issue of number of valid clusters in a dataset is also discussed. The hyper dimensional chemical datasets are traditionally been treated only with the help of conventional clustering methods like hierarchical and non-hierarchical methods. In this paper we look into the issue of clustering these chemical datasets with fuzzy paradigms. In this paper a number of fuzzy clustering approaches like fuzzy c-mean, Gustafson and Kessel , Gath and Geva, fuzzy c-varieties, adaptive fuzzy , fuzzy based c-shell algorithms and some other aspects of fuzzy clustering are discussed.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||fuzzy c-mean, clustering, chemoinformatics, neural network|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System|
|Deposited By:||Ms Haslina Hashim|
|Deposited On:||23 May 2007 04:03|
|Last Modified:||19 Jan 2012 00:32|
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