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A new error rate estimator for small sample sized problems / Ahmed Said Mohammed Hefny ; Supervised Amir Atiya

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Said Mohammed Hefny , 2010Description: 64P. : charts ; 30cmOther title:
  • أسلوب جديد لتقدير معدل الخطأ فى التصنيف للعينات الصغيرة [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: Estimating the classification error rate a classifier is a key issue in machine learning . Such estimation is needed for comparing classifers tuning the parameters of a parameterized classifier or feature selection . Several methods have been proposed to estimate error rate most of which rely on partitioning the data set or drawing bootstrap samples therefrom
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2010.Ah.N (Browse shelf(Opens below)) Not for loan 01010110054117000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2010.Ah.N (Browse shelf(Opens below)) 54117.CD Not for loan 01020110054117000

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

Estimating the classification error rate a classifier is a key issue in machine learning . Such estimation is needed for comparing classifers tuning the parameters of a parameterized classifier or feature selection . Several methods have been proposed to estimate error rate most of which rely on partitioning the data set or drawing bootstrap samples therefrom

Issued also as CD

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