一种新的基于核原型的学习算法

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. Pub Date : 2004-08-23 DOI:10.1109/ICPR.2004.1333849

A. K. Qin, P. N. Suganthan

{"title":"一种新的基于核原型的学习算法","authors":"A. K. Qin, P. N. Suganthan","doi":"10.1109/ICPR.2004.1333849","DOIUrl":null,"url":null,"abstract":"We propose a novel kernel prototype-based learning algorithm, called kernel generalized learning vector quantization (KGLYQ) algorithm, which can significantly improve the classification performance of the original generalized learning vector quantization algorithm in complex pattern classification tasks. In addition, the KGLVQ can also serve as a good general kernel learning framework for further investigation.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":"{\"title\":\"A novel kernel prototype-based learning algorithm\",\"authors\":\"A. K. Qin, P. N. Suganthan\",\"doi\":\"10.1109/ICPR.2004.1333849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel kernel prototype-based learning algorithm, called kernel generalized learning vector quantization (KGLYQ) algorithm, which can significantly improve the classification performance of the original generalized learning vector quantization algorithm in complex pattern classification tasks. In addition, the KGLVQ can also serve as a good general kernel learning framework for further investigation.\",\"PeriodicalId\":335842,\"journal\":{\"name\":\"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"58\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2004.1333849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2004.1333849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 58

摘要

本文提出了一种新的基于核原型的学习算法——核广义学习向量量化(KGLYQ)算法，该算法在复杂模式分类任务中显著提高了原有广义学习向量量化算法的分类性能。此外，KGLVQ还可以作为一个很好的通用核学习框架，用于进一步的研究。

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

A novel kernel prototype-based learning algorithm

We propose a novel kernel prototype-based learning algorithm, called kernel generalized learning vector quantization (KGLYQ) algorithm, which can significantly improve the classification performance of the original generalized learning vector quantization algorithm in complex pattern classification tasks. In addition, the KGLVQ can also serve as a good general kernel learning framework for further investigation.

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

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.

自引率

0.00%

发文量