Relaxation-based structure learning of dynamic bayesian Networks / Farida Mohamed Sabry Elsayed ; Supervised Nevin M. Darwish , Magda B. Fayek

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Farida Mohamed Sabry Elsayed

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TextLanguage: English Publication details: Cairo : Farida Mohamed Sabry Elsayed , 2009Description: 114 P. : plans ; 25cmOther title:

تعلم هياكل شبكات بيزيان الديناميكية باسلوب الارخاء [Added title page title]

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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: Learning DBN structures from data is a relatively new research direction. This work uses probabilistic relaxation for learning dynamic bayesian network structures from data. The existence of an edge in the network is not considered as a hard or deterministic issue, but rather we assign a certain probability for the existence of each edge

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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	Cai01.13.06.M.Sc.2009.Fa.R (Browse shelf(Opens below))		Not for loan		01010110051382000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.06.M.Sc.2009.Fa.R (Browse shelf(Opens below))	51382.CD	Not for loan		01020110051382000

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Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering

Learning DBN structures from data is a relatively new research direction. This work uses probabilistic relaxation for learning dynamic bayesian network structures from data. The existence of an edge in the network is not considered as a hard or deterministic issue, but rather we assign a certain probability for the existence of each edge

Issued also as CD

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