大字符集识别中的误差界估计与特征选择

[1988 Proceedings] 9th International Conference on Pattern Recognition Pub Date : 1988-11-14 DOI:10.1109/ICPR.1988.28482

Xiao Huang, Yuo-Shou Wu, Xiaoqing Ding

{"title":"大字符集识别中的误差界估计与特征选择","authors":"Xiao Huang, Yuo-Shou Wu, Xiaoqing Ding","doi":"10.1109/ICPR.1988.28482","DOIUrl":null,"url":null,"abstract":"Based on the reduction of entropy, the analysis of the estimation of error bounds is discussed. This estimation is simple in computation and is associated with a scatter matrix of classes. For the case of a large character set, a novel definition of separability of classes is proposed. It is simple in computation and can be used to evaluate error bounds and to choose a subset of features with minimum loss of information.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The estimation of error bounds and feature selection in large character set recognition\",\"authors\":\"Xiao Huang, Yuo-Shou Wu, Xiaoqing Ding\",\"doi\":\"10.1109/ICPR.1988.28482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the reduction of entropy, the analysis of the estimation of error bounds is discussed. This estimation is simple in computation and is associated with a scatter matrix of classes. For the case of a large character set, a novel definition of separability of classes is proposed. It is simple in computation and can be used to evaluate error bounds and to choose a subset of features with minimum loss of information.<<ETX>>\",\"PeriodicalId\":314236,\"journal\":{\"name\":\"[1988 Proceedings] 9th International Conference on Pattern Recognition\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1988 Proceedings] 9th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1988.28482\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1988 Proceedings] 9th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.1988.28482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

在熵约化的基础上，讨论了误差界估计的分析。这种估计计算简单，并与类的散点矩阵相关联。针对大字符集的情况，提出了类可分性的新定义。它计算简单，可用于评估误差边界，并选择具有最小信息损失的特征子集。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

The estimation of error bounds and feature selection in large character set recognition

Based on the reduction of entropy, the analysis of the estimation of error bounds is discussed. This estimation is simple in computation and is associated with a scatter matrix of classes. For the case of a large character set, a novel definition of separability of classes is proposed. It is simple in computation and can be used to evaluate error bounds and to choose a subset of features with minimum loss of information.<>

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

[1988 Proceedings] 9th International Conference on Pattern Recognition

自引率

0.00%

发文量