Bootstrapping for efficient handwritten digit recognition

被引：10
|
作者：
Saradhi, VV [1 ]
Murty, MN [1 ]
机构：
[1] Indian Inst Sci, Dept Comp Sci & Automat, Bangalore 560012, Karnataka, India
来源：
PATTERN RECOGNITION | 2001年 / 34卷 / 05期
关键词：
bootstrapping; redundancy removal; condensed nearest neighbor; prototype selection; genetic algorithms; thresholding; classification accuracy;
D O I：
10.1016/S0031-3203(00)00043-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we present two algorithms for selecting prototypes from the given training data set. Here, we employ the bootstrap technique to preprocess the data. We compare the proposed algorithms with the condensed nearest-neighbor algorithm which is order dependent and a genetic-algorithm-based prototype selection scheme which is order independent. Algorithms proposed in this paper are found to be better than the condensed nearest neighbor and prototype selection methods in terms of classification accuracy. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：1047 / 1056
页数：10
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