摘要
利用神经网络分类器组合 ,对手写体数字识别问题进行了研究 .通过对同一训练样本集抽取不同特征集合 ,从而获得不同的神经网络分类器 .对这些分类器的分类结果组合得到最终的分类结果 .提出性能函数 PF(S,T)用来确定阈值 S,T,从而获得错误率与拒识率间的最佳平衡 .实验结果表明 ,此种分类器组合方法能根据不同应用的要求 ,自动地选取性能函数中的参数 ,减少分类错误率 ,提高识别的可靠性 .
A neural network classifier combination method is introduced in this paper and applied to handwritten numeral recognition. Different kinds of feature sets are extracted from the same sample set and different classifiers are obtained from these feature sets. Performance function PF(S,T) is introduced to determine the two thresholds S and T which are used to obtain the best balance between error rate and reject rate. Experiment results demonstrate that this combination method can adjust PF's parameters according to different application's requirement, reduce classifying error rate, and improve recognition reliability.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2000年第12期1488-1492,共5页
Journal of Computer Research and Development
关键词
神经网络分类器
分类器组合
字符识别
neural network classifier
classifier combination
handwritten numeral recognition
