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Support vector machines in handwritten digits classification

被引：4
|
作者：
Markowska-Kaczmar, U [1 ]
Kubacki, P [1 ]
机构：
[1] Wroclaw Tech Univ, Inst Appl Informat, PL-50370 Wroclaw, Poland
来源：
5th International Conference on Intelligent Systems Design and Applications, Proceedings | 2005年
关键词：
D O I：
10.1109/ISDA.2005.87
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the paper our approach to classify handwritten digits by using Support Vector Machines is described. Because of the unsatisfying, long time of training of SVM we propose to apply k-nearest neighbours algorithm with Manhattan distance to obtain reduced size of training set having a hope that this hybrid method does not make the significantly worse results of recognition, The aim of presented further experiments was to verify this assumption.
引用
收藏
页码：406 / 411
页数：6
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