Experimental analysis of traditional classification algorithms on bio medical dtatasets

Shobha Aswal, N. J. Ahuja, Ritika
{"title":"Experimental analysis of traditional classification algorithms on bio medical dtatasets","authors":"Shobha Aswal, N. J. Ahuja, Ritika","doi":"10.1109/NGCT.2016.7877478","DOIUrl":null,"url":null,"abstract":"Data classification in medical field is distinct from that in other fields, because the medical data are heterogeneous, skewed and complex in nature and medical data classification involves multi class classification. In this paper we present the experimental analysis of well-known traditional classification algorithms on bio-medical datasets in order to observe their performance. This experimental analysis will provide deeper insight in designing the efficient classification algorithm for bio medical data.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGCT.2016.7877478","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Data classification in medical field is distinct from that in other fields, because the medical data are heterogeneous, skewed and complex in nature and medical data classification involves multi class classification. In this paper we present the experimental analysis of well-known traditional classification algorithms on bio-medical datasets in order to observe their performance. This experimental analysis will provide deeper insight in designing the efficient classification algorithm for bio medical data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
生物医学数据集传统分类算法的实验分析
医学领域的数据分类不同于其他领域,因为医学数据具有异质性、偏斜性和复杂性,医学数据分类涉及多类分类。本文对传统的生物医学分类算法在生物医学数据集上的性能进行了实验分析。这一实验分析将为设计高效的生物医学数据分类算法提供更深入的见解。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
SCADA security issues and FPGA implementation of AES — A review Real-time analysis and visualization of online social media dynamics An advanced clustering scheme for wireless sensor networks using particle swarm optimization Physical telepresence: Growth trends of Tangible User Interface and its future Capital market forecasting by using sentimental analysis
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1