Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem

Marcin Grochowina, L. Leniowska
{"title":"Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem","authors":"Marcin Grochowina, L. Leniowska","doi":"10.15439/2015F194","DOIUrl":null,"url":null,"abstract":"The paper presents a concise report on the comparison of the classifiers k-NN and SVM in the case of a fuzzy classification of the arterio-venous fistula based on audio recordings. What has been used in the studies are the acoustic signals taken from both healthy patients as well as those diagnosed with the narrowing of a fistula in a mild and major degree of stenosis. In the publication there have been selected two features, each presenting one- time and frequency domain, which enable a quite clear depiction of the classification result. The aim of the study is to develop a solution enabling the detection of fistula's pathologies at an early stage.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15439/2015F194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

The paper presents a concise report on the comparison of the classifiers k-NN and SVM in the case of a fuzzy classification of the arterio-venous fistula based on audio recordings. What has been used in the studies are the acoustic signals taken from both healthy patients as well as those diagnosed with the narrowing of a fistula in a mild and major degree of stenosis. In the publication there have been selected two features, each presenting one- time and frequency domain, which enable a quite clear depiction of the classification result. The aim of the study is to develop a solution enabling the detection of fistula's pathologies at an early stage.
SVM与k-NN分类器在动静脉瘘状态估计中的比较
本文简要介绍了分类器k-NN和SVM在基于录音的动静脉瘘模糊分类中的比较。研究中使用的是健康患者以及诊断为轻度和重度瘘管狭窄的患者的声信号。在出版物中,选择了两个特征,每个特征都呈现一个时域和频域,这使得对分类结果的描述非常清晰。该研究的目的是开发一种解决方案,使瘘的病理检测在早期阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信