| 000 | 01433cam a2200301 a 4500 | ||
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| 003 | EG-GiCUC | ||
| 008 | 101026s2010 ua d f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.06.M.Sc.2010.Ah.N | ||
| 100 | 0 | _aAhmed Said Mohammed Hefny | |
| 245 | 1 | 2 |
_aA new error rate estimator for small sample sized problems / _cAhmed Said Mohammed Hefny ; Supervised Amir Atiya |
| 246 | 1 | 5 | _aأسلوب جديد لتقدير معدل الخطأ فى التصنيف للعينات الصغيرة |
| 260 |
_aCairo : _bAhmed Said Mohammed Hefny , _c2010 |
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| 300 |
_a64P. : _bcharts ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering | ||
| 520 | _aEstimating 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 | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aError Rate Estimation | |
| 653 | 4 | _aParzen Windows | |
| 653 | 4 | _aPattern Classification | |
| 700 | 0 |
_aAmir Atiya , _eSupervisor |
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| 905 |
_aFatma _eCataloger |
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| 905 |
_aNazla _eRevisor |
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| 942 |
_2ddc _cTH |
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| 999 |
_c31875 _d31875 |
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