dc.contributor.author	Mohammed, Mustafa Ahmed
dc.contributor.author	Supervisor - Mohamed Elhafiz Mustafa Musa
dc.date.accessioned	2014-03-10T11:19:25Z
dc.date.available	2014-03-10T11:19:25Z
dc.date.issued	2013-06-01
dc.identifier.citation	Mohammed,Mustafa Ahmed.Comparison of Two Clustering Techniques Case Study: Breast Cancer Data/ Mustafa Ahmed Mohammed؛ Mohamed Elhafiz Mustafa .-Khartoum : sudan university of science and technology,computer science,2013.-71p:ill;28cm.-M.Sc.	en_US
dc.identifier.uri	http://repository.sustech.edu/handle/123456789/3844
dc.description	Thesis	en_US
dc.description.abstract	The main goal of this thesis is to study two clustering methods practically. The aims of practical study are to find out the capabilities of these two methods in clustering the breast cancer data set. Many clusters have been generated using both k-means and Two-step. Extensive comparisons have been conducted. The main conclusion is that these two methods generate different clusters. The main reason could be the difference in their strategies. Further, studies are needed to find more reasons.	en_US
dc.description.sponsorship	sudan university of scince and technology	en_US
dc.language.iso	en	en_US
dc.publisher	Sudan University of Science and Technology	en_US
dc.subject	clustering	en_US
dc.subject	technigues	en_US
dc.subject	Breast cancer	en_US
dc.subject	Data processing	en_US
dc.title	Comparison of Two Clustering Techniques Case Study: Breast Cancer Data	en_US
dc.type	Thesis	en_US

Comparison of Two Clustering Techniques Case Study: Breast Cancer Data

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