...
首页> 外文期刊>Journal of Basic and Applied Sciences >Lifescience Global :: Abstract : Classification Techniques in Machine Learning: Applications and Issues
【24h】

Lifescience Global :: Abstract : Classification Techniques in Machine Learning: Applications and Issues

机译:全球生命科学::摘要:机器学习中的分类技术:应用程序和问题

获取原文

摘要

 Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic classification techniques. Later we discuss some major types of classification method including Bayesian networks, decision tree induction, k-nearest neighbor classifier and Support Vector Machines (SVM) with their strengths, weaknesses, potential applications and issues with their available solution. The goal of this study is to provide a comprehensive review of different classification techniques in machine learning. This work will be helpful for both academia and new comers in the field of machine learning to further strengthen the basis of classification methods.
机译:分类是一种数据挖掘(机器学习)技术,用于预测数据实例的组成员身份。有几种分类技术可用于分类目的。在本文中,我们介绍了基本的分类技术。稍后,我们将讨论一些主要类型的分类方法,包括贝叶斯网络,决策树归纳,k最近邻分类器和支持向量机(SVM),它们的优点,缺点,潜在的应用以及可用解决方案的问题。这项研究的目的是对机器学习中不同分类技术进行全面综述。这项工作将为机器学习领域的学术界和新来者提供帮助,进一步加强分类方法的基础。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号