Hybrid optimization techniques for cancer diagnosis models / Nermeen Kamel Abdelmoniem ; Supervised L . F . Abdelal , N . H . Sweilam , A . A . Tharwat
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TextLanguage: English Publication details: Cairo : Nermeen Kamel Abdelmoniem , 2010Description: 90P. : charts , facsimiles ; 25cmOther title: - التقنيات الامثلية المهجنه لتشخيص مرض السرطان [Added title page title]
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.12.17.M.Sc.2010.Ne.H (Browse shelf(Opens below)) | Not for loan | 01010110054655000 | ||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.12.17.M.Sc.2010.Ne.H (Browse shelf(Opens below)) | 54655.CD | Not for loan | 01020110054655000 |
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| Cai01.12.17.M.Sc.2010.Ah.H Higgs mechanism in warped extra dimension / | Cai01.12.17.M.Sc.2010.Ay.M Multigrid - finite element method for partial differential equations and their optimal control / | Cai01.12.17.M.Sc.2010.Ay.M Multigrid - finite element method for partial differential equations and their optimal control / | Cai01.12.17.M.Sc.2010.Ne.H Hybrid optimization techniques for cancer diagnosis models / | Cai01.12.17.M.Sc.2010.Ne.H Hybrid optimization techniques for cancer diagnosis models / | Cai01.12.17.M.Sc.2010.Sa.A Asymptotic behavior of non-linear difference equation / | Cai01.12.17.M.Sc.2010.Sa.A Asymptotic behavior of non-linear difference equation / |
Thesis (M.Sc.) - Cairo University - Faculty of Science - Department of Mathematics
Suport vector machine has become an increasingly popular tool for machine learning tasks involving classification regression or novelty detection . Training a support vector machine requires the solution of a very large quadratic programming problem . Ttaditional optimization methods cannot be directly applied due to memory restrictions . Up to now several approaches exist for circumventing the above shortcomings and work well
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