A mathematical programming approach for selection of variables in cluster analysis / Safia Mahmoud Ezzat Mohallal ; Supervised Nadia M. Girgis , Mohamed S. A. Osman , Mahmoud M. Rashwan

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Safia Mahmoud Ezzat Mohallal

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TextLanguage: English Publication details: Cairo : Safia Mahmoud Ezzat Mohallal , 2011Description: 82 P. ; 25cmOther title:

استخدام البرمجة الرياضية فى اختيار المتغيرات فى التحليل العنقودى [Added title page title]

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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics Summary: Data clustering is a common technique for statistical data amnalysis it is defined as a class of statistical techniques for classifing a set of observations into completely different groups . Cluster analysis seeks to minimize group variance and maximize between group variance . In this study we formulate a mathematical programming model that chooses the most important variables in cluster analysis

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Item type	Current library	Home library	Call number	Copy number	Status	Date due	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.03.01.M.Sc.2011.Sa.M (Browse shelf(Opens below))		Not for loan		01010110055485000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.03.01.M.Sc.2011.Sa.M (Browse shelf(Opens below))	55485.CD	Not for loan		01020110055485000

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Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics

Data clustering is a common technique for statistical data amnalysis it is defined as a class of statistical techniques for classifing a set of observations into completely different groups . Cluster analysis seeks to minimize group variance and maximize between group variance . In this study we formulate a mathematical programming model that chooses the most important variables in cluster analysis

Issued also as CD

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