An Overview of Supervised Machine Learning Algorithm

Vratika Gupta, V. Mishra, Priyank Singhal, Amit Kumar
{"title":"An Overview of Supervised Machine Learning Algorithm","authors":"Vratika Gupta, V. Mishra, Priyank Singhal, Amit Kumar","doi":"10.1109/SMART55829.2022.10047618","DOIUrl":null,"url":null,"abstract":"Machine learning is a subset of Artificial intelligence. Algorithms for machine learning automatically learn from experience and improve from it without being explicitly programmed. Machine learning defines Supervised, Unsupervised and Reinforcement Learning. Supervised algorithms are worked on under guidance but unsupervised algorithms are worked on without guidance. Machine learning provides good accuracy in both the algorithms. This paper is describing machine learning methods, different types of supervised learning algorithms, comparison of machine learning algorithms and application of machine learning algorithms.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART55829.2022.10047618","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

Machine learning is a subset of Artificial intelligence. Algorithms for machine learning automatically learn from experience and improve from it without being explicitly programmed. Machine learning defines Supervised, Unsupervised and Reinforcement Learning. Supervised algorithms are worked on under guidance but unsupervised algorithms are worked on without guidance. Machine learning provides good accuracy in both the algorithms. This paper is describing machine learning methods, different types of supervised learning algorithms, comparison of machine learning algorithms and application of machine learning algorithms.
监督式机器学习算法综述
机器学习是人工智能的一个子集。机器学习算法可以自动从经验中学习并从中改进,而无需明确编程。机器学习定义了监督学习、无监督学习和强化学习。监督算法是在指导下进行的,而非监督算法是在没有指导的情况下进行的。机器学习在这两种算法中都提供了良好的准确性。本文描述了机器学习的方法、不同类型的监督学习算法、机器学习算法的比较以及机器学习算法的应用。
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