Visualisasi Algoritma sebagai Sarana Pembelajaran K-Means Clustering

Alethea Suryadibrata, Julio Christian Young
{"title":"Visualisasi Algoritma sebagai Sarana Pembelajaran K-Means Clustering","authors":"Alethea Suryadibrata, Julio Christian Young","doi":"10.31937/TI.V12I1.1523","DOIUrl":null,"url":null,"abstract":"Algorithm Visualization (AV) is often used in computer science to represents how an algorithm works. Educators believe that visualization can help students to learn difficult algorithms. In this paper, we put our interest in visualizing one of Machine Learning (ML) algorithms. ML algorithms are used in various fields. Some of the algorithms are used to classify, predict, or cluster data. Unfortunately, many students find that ML algorithms are hard to learn since some of these algorithms include complicated mathematical equations. We hope this research can help computer science students to understand K-Means Clustering in an easier way.","PeriodicalId":347196,"journal":{"name":"Ultimatics : Jurnal Teknik Informatika","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ultimatics : Jurnal Teknik Informatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31937/TI.V12I1.1523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Algorithm Visualization (AV) is often used in computer science to represents how an algorithm works. Educators believe that visualization can help students to learn difficult algorithms. In this paper, we put our interest in visualizing one of Machine Learning (ML) algorithms. ML algorithms are used in various fields. Some of the algorithms are used to classify, predict, or cluster data. Unfortunately, many students find that ML algorithms are hard to learn since some of these algorithms include complicated mathematical equations. We hope this research can help computer science students to understand K-Means Clustering in an easier way.
可视化算法作为学习的手段
算法可视化(Algorithm Visualization, AV)在计算机科学中经常用于表示算法是如何工作的。教育工作者认为,可视化可以帮助学生学习困难的算法。在本文中,我们把我们的兴趣放在可视化机器学习(ML)算法之一。机器学习算法应用于各个领域。其中一些算法用于对数据进行分类、预测或聚类。不幸的是,许多学生发现机器学习算法很难学习,因为其中一些算法包含复杂的数学方程。我们希望这项研究可以帮助计算机科学专业的学生更容易地理解K-Means聚类。
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:481959085
Book学术官方微信